A hospital management system

Abstract

The embodiment of the specification provides a system for hospital management, comprising a manager terminal configured to present an interface for a user to manage an intelligent agent of a hospital; a processing device in communication connection with the manager terminal, wherein: the intelligent agent comprises a software entity constructed based on artificial intelligence technology and self-evolved, which is realized through the processing device, the interface is configured to present a virtual character, the user queries and updates basic configuration data of the intelligent agent by interacting with the virtual character, the basic configuration data comprises at least one of a dictionary, a knowledge database and a template, and the processing device is configured to receive updated basic configuration data input by the user via the interface from the manager terminal, and provide user services based on the updated basic configuration data by using the intelligent agent.

Description

[0001] Cross-referencing

[0002] This application claims priority to international application No. PCT / CN2024 / 109060, filed on July 31, 2024, the full contents of which are incorporated herein by reference. Technical Field

[0003] This manual relates to hospital systems, and more particularly to a hospital management system. Background Technology

[0004] Hospital management involves overseeing hospitals and their medical facilities at both administrative and operational levels (e.g., administrative management, clinical management, financial management, operational management, human resource management, etc.) to ensure that healthcare services are provided effectively and efficiently to users. An effective hospital management system is crucial for hospital operations. Therefore, we need to develop an effective and reliable hospital management system. Summary of the Invention

[0005] One embodiment of this specification provides a system for hospital management, the system comprising: a manager terminal configured to present an interface for users to manage hospital intelligent agents; and a processing device communicatively connected to the manager terminal, wherein: the intelligent agent comprises a software entity built and self-evolving based on artificial intelligence technology, implemented by the processing device; the interface is configured to present a virtual character; the user interacts with the virtual character to query and update basic configuration data of the intelligent agent; the basic configuration data includes at least one of a dictionary, a knowledge database, and a template; and the processing device is configured to receive updated basic configuration data input by the user through the interface from the manager terminal, and to provide user services based on the updated basic configuration data using the intelligent agent.

[0006] In some embodiments, the interface is further configured to present operational metrics of the agent, including at least one of the following: the number of users served by the agent, the number of services provided by the agent, the amount of data processed by the agent, and the service quality of the agent.

[0007] In some embodiments, at least a portion of the agents are further generated based on natural language processing algorithms.

[0008] In some embodiments, the intelligent agent includes intelligent agents corresponding to different types of medical service providers, intelligent agents corresponding to different hospital departments, intelligent agents corresponding to different medical service processes, and intelligent agents corresponding to different user services.

[0009] In some embodiments, the intelligent agent includes a first intelligent agent corresponding to a medical service process. The first intelligent agent is configured to: monitor updates to data related to the patient's medical service process; in response to detecting that the data related to the medical service process includes updated data, perform an event of interest detection based on the updated data; and in response to detecting the occurrence of the event of interest, perform a preset operation corresponding to the event of interest to provide user services to relevant users of the medical service process, wherein the event of interest detection and / or the preset operation are performed according to updated basic configuration data corresponding to the first intelligent agent.

[0010] In some embodiments, performing the detection of events of interest based on the updated data includes: determining the current stage of the patient's medical service process; determining type information of events of interest to be detected based on the patient's current stage; and performing the detection of events of interest on the updated data based on the type information.

[0011] In some embodiments, performing interest event detection based on the updated data includes: determining type information of the interest event to be detected based on the hardware device corresponding to the updated data; and performing interest event detection on the updated data based on the type information.

[0012] In some embodiments, the detection of events of interest is based on a rule for detecting events of interest, which is learned by the first agent from historical records and the updated basic configuration data.

[0013] In some embodiments, the preset operation corresponding to the event of interest is determined based on the correspondence between the event of interest and the preset operation, and the correspondence is learned by the first agent from historical records and the updated basic configuration data.

[0014] In some embodiments, the intelligent agent includes a second intelligent agent, which is configured to implement user services related to certain stages in a medical service process. The second intelligent agent is configured to: acquire data related to the patient's stage; process the data based on the updated basic configuration data of the second intelligent agent; and provide the user services to the relevant users of the stage based on the processing results.

[0015] In some embodiments, the user service is obtained through a user space application installed on the user terminal, and the virtual character corresponding to the second intelligent agent is presented through the user space application. The user service is provided to the relevant user based on the interaction between the relevant user and the virtual character corresponding to the second intelligent agent.

[0016] In some embodiments, the second intelligent agent includes a pre-consultation intelligent agent corresponding to the pre-consultation service. The pre-consultation intelligent agent is configured to: conduct a pre-consultation inquiry with the patient through the patient's patient terminal based on the department of the doctor the patient registered with; and generate the pre-consultation record based on the data collected by the patient terminal in the pre-consultation inquiry.

[0017] In some embodiments, determining the content of the pre-consultation inquiry based on the department of the doctor the patient registered with includes: obtaining the pre-consultation record template corresponding to the department of the doctor and the known information of the patient; determining any missing information that has not yet been collected in the pre-consultation record template by comparing the pre-consultation record template and the known information of the patient; and determining the inquiry content based on the missing information.

[0018] In some embodiments, the content of the pre-consultation inquiry is determined based on the department of the doctor to which the patient registered, including: using a missing information determination model to process known information of the department of the doctor and the patient to determine missing information to be collected from the patient; and using an inquiry content determination model to process the missing information to determine the inquiry content, wherein the missing information determination model and the inquiry content determination model are trained machine learning models.

[0019] In some embodiments, the pre-consultation inquiry is based on the inquiry content and includes multiple rounds of inquiry. The inquiry content includes the inquiry content of each round of inquiry. Initiating the pre-consultation inquiry to the patient includes: for each round of pre-consultation inquiry except for the first round of inquiry, determining the semantic and emotional information of the patient's historical answers based on data collected before the current round of inquiry; adjusting the inquiry content of the current round of inquiry based on the semantic and emotional information; and conducting the current round of inquiry through the patient's terminal based on the adjusted inquiry content of the current round of inquiry.

[0020] In some embodiments, the pre-consultation includes multiple rounds of questioning. The pre-consultation questioning of the patient includes: for each current round of questioning other than the first round of questioning, determining the question content corresponding to the current round of questioning based on the question content of historical questions, the patient's historical answers, and the patient's known information, using a question content determination model, wherein the question content determination model is a trained machine learning model; and conducting the current round of questioning through the patient terminal based on the question content corresponding to the current round of questioning.

[0021] In some embodiments, the second intelligent agent includes a consultation intelligent agent corresponding to the consultation service. The consultation intelligent agent is configured to: determine whether the patient needs to communicate with a remote companion based on the sensing information collected by the sensing device during the consultation process; and in response to determining that the patient needs to communicate with the remote companion, control at least one terminal device to enlarge the interface elements related to the remote companion service.

[0022] In some embodiments, the second intelligent agent includes an inpatient intelligent agent corresponding to inpatient services. The inpatient intelligent agent is configured to: determine whether a patient meets the conditions for admission examination in the ward based on sensing information collected by sensing devices in the ward; in response to determining that the patient meets the conditions for admission examination, control an intelligent nursing cart to guide a nurse into the ward, and control the intelligent nursing cart to present information related to the admission examination; and generate an admission record based on the patient's physical examination data collected during the admission examination.

[0023] In some embodiments, the second intelligent agent includes a hospitalization intelligent agent corresponding to hospitalization services. The hospitalization intelligent agent is configured to: determine the patient's daily plan for each day of hospitalization based on the patient's patient data and the doctor's medical orders for the patient. The daily plan includes at least one medical operation that needs to be performed on the patient that day. The daily plan is displayed to the patient through a terminal device in the patient's ward. The daily plan is also displayed to the nurse through a terminal device corresponding to the patient.

[0024] In some embodiments, the second intelligent agent includes a surgical intelligent agent corresponding to the surgical service, the surgical intelligent agent being configured to: determine a planned route from the patient's current location to the operating room waiting area; control an intelligent wheelchair to transport the patient along the planned route to the waiting area; during the transport of the patient to the waiting area, provide preoperative education to the patient based on the patient's patient data and surgical plan using an XR device worn by the patient; and after the patient is transported to the waiting area, verify the patient's identity based on the patient's biometric information collected by sensing devices in the waiting area.

[0025] In some embodiments, the intelligent agent is an embodied intelligent agent comprising a physical entity and the software entity, the software entity being configured to control at least a portion of the physical components of the physical entity to provide user services.

[0026] One embodiment of this specification provides a system for hospital management. The system includes: a manager terminal configured to present an interface for users to manage a digital twin of the hospital. The digital twin maps the state of associated physical entities and is generated based on a preset data structure. The digital twin includes a first digital twin and a second digital twin. The second digital twin can be updated through the interface. For the first digital twin, the mapping of the state of the associated physical entities includes: the first digital twin is updated based on updates to the state of the associated physical entities. For the second digital twin, the mapping of the state of the associated physical entities includes: the associated physical entities are updated based on updates to the second digital twin.

[0027] In some embodiments, the update of the state of the associated physical entity is obtained based on the real-time information detection of the associated physical entity.

[0028] In some embodiments, the real-time information includes at least one of the following: information collected by the hospital's sensing devices, information collected by user terminals associated with the hospital, and information collected by medical service devices.

[0029] In some embodiments, the first digital twin includes a digital twin corresponding to a public area of ​​the hospital, the digital twin corresponding to the public area reflecting a digital twin view of the public area, the digital twin view displaying a real-time 3D map and monitoring indicators of the public area.

[0030] In some embodiments, the first digital twin includes a digital twin corresponding to a medical service, the digital twin of which reflects the operational metrics of the medical service.

[0031] In some embodiments, for at least a portion of the first digital twin, in response to detecting that an update to the state of the associated physical entity is normal, the first digital twin is updated in a first manner; in response to detecting that an update to the state of the associated physical entity is abnormal, the first digital twin is updated in a second manner; and the first manner is different from the second manner.

[0032] In some embodiments, the second digital twin includes a digital twin corresponding to a hardware device, the digital twin of which reflects the parameters of the hardware device.

[0033] In some embodiments, the system further includes a processing device configured to: receive update information of a digital twin corresponding to the hardware device from an administrator terminal that presents the interface; store the update information in a storage device; and send an update notification to the hardware device, causing the hardware device to retrieve the update information from the storage device to update its configuration.

[0034] In some embodiments, the processing device includes software modules for providing user services. Each software module subscribes to update notifications of configuration parameters of a corresponding hardware device. The correspondence between the software modules and the configuration parameters of the hardware devices is learned by the agent based on historical data from the hospital.

[0035] In some embodiments, the second digital twin includes a digital twin corresponding to the user service, the digital twin of the user service reflecting the parameters of the user service.

[0036] In some embodiments, the second digital twin includes a digital twin corresponding to a medical service process. The digital twin corresponding to the medical service process reflects the parameters of the medical service process. The parameters include the standard operating procedures of the medical service process. The standard operating procedures specify the standard steps of the medical service process and their corresponding data acquisition protocols.

[0037] In some embodiments, the interface is configured to present a virtual character that is configured to engage in a conversation with a user; and interface elements that are used to initiate the conversation with the virtual character.

[0038] In some embodiments, the content displayed on the interface is updated based on the content of the session.

[0039] Some additional features of this specification will be described in the following description. To more clearly illustrate the technical solutions of the embodiments of this specification through study of the following description and corresponding drawings, or through the examples, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this specification. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. The features of this specification can be implemented and achieved through practice or by using the various methods, tools, and combinations discussed in detail below. Attached Figure Description

[0040] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0041] Figure 1 This is a block diagram of an exemplary medical service system according to some embodiments of this specification;

[0042] Figure 2 These are schematic diagrams of exemplary medical service systems shown in some embodiments of this specification;

[0043] Figure 3 This is a schematic diagram of an exemplary hospital support platform according to some embodiments of this specification;

[0044] Figure 4 This is a schematic diagram of a hospital management system according to some embodiments of this specification;

[0045] Figure 5 These are schematic diagrams of interfaces shown according to some embodiments of this specification;

[0046] Figure 6 These are schematic diagrams of exemplary digital twins according to some embodiments of this specification;

[0047] Figure 7A This is a schematic diagram of a digital twin view of a check-in area according to some embodiments of this specification;

[0048] Figure 7B This is a schematic diagram of a digital twin view of a waiting room according to some embodiments of this specification;

[0049] Figure 7C This is a schematic diagram of a digital twin view of the consultation area according to some embodiments of this specification;

[0050] Figure 7D This is based on some embodiments shown in this specification. Figure 7C A schematic diagram of the digital twin view of the consultation room in the consultation area;

[0051] Figure 7E This is a schematic diagram of a digital twin view of a surgical area according to some embodiments of this specification;

[0052] Figure 7F This is based on some embodiments shown in this specification. Figure 7E A schematic diagram of a digital twin view of the operating room in the mid-operative area;

[0053] Figure 8AThis is a schematic diagram of a digital twin corresponding to outpatient registration services, as shown in some embodiments of this specification;

[0054] Figure 8B These are schematic diagrams of digital twins corresponding to treatment and care services, as shown in some embodiments of this specification;

[0055] Figure 8C These are schematic diagrams of digital twins corresponding to routine surgical procedures, as shown in some embodiments of this specification.

[0056] Figure 8D These are schematic diagrams of digital twins corresponding to medical consultation services, as shown in some embodiments of this specification.

[0057] Figure 8E These are schematic diagrams of digital twins corresponding to inpatient services, as shown in some embodiments of this specification;

[0058] Figure 8F These are schematic diagrams of digital twins corresponding to departmental surgical services, as shown in some embodiments of this specification;

[0059] Figure 9A These are schematic diagrams of display devices in a waiting room, as shown in some embodiments of this specification;

[0060] Figure 9B These are schematic diagrams of a display device in an examination room according to some embodiments of this specification;

[0061] Figure 9C This is a schematic diagram of a display device in an inpatient ward according to some embodiments of this specification;

[0062] Figure 9D This is a schematic diagram of a display device in a surgical waiting area according to some embodiments of this specification;

[0063] Figure 10 This is a schematic diagram of an exemplary process for updating the configuration of a hardware device according to some embodiments of this specification;

[0064] Figure 11 This is a schematic diagram of an interface for presenting information related to an intelligent agent, according to some embodiments of this specification;

[0065] Figure 12 This is a schematic diagram of an exemplary process for providing user services to relevant users of a medical service process using a first intelligent agent, as shown in some embodiments of this specification.

[0066] Figure 13This is a schematic diagram illustrating an exemplary process of using a second intelligent agent to provide user services to relevant users according to some embodiments of this specification;

[0067] Figure 14A This is a schematic diagram of an exemplary process for providing pre-consultation services according to some embodiments of this specification;

[0068] Figure 14B This is a schematic diagram of an exemplary process for making a second inquiry according to some embodiments of this specification;

[0069] Figure 15 This is a schematic diagram of an exemplary process for providing medical outpatient services based on perceived information, according to some embodiments of this specification;

[0070] Figure 16 This is a schematic diagram of an exemplary process for providing services to relevant users during the admission process, as shown in some embodiments of this specification;

[0071] Figure 17 This is a schematic diagram of an exemplary process for providing care services according to some embodiments of this specification;

[0072] Figure 18 These are schematic diagrams illustrating the preoperative guidance process according to some embodiments of this specification; and

[0073] Figure 19 This is a schematic diagram illustrating an exemplary procedure for performing surgery according to some embodiments of this specification. Detailed Implementation

[0074] In the following detailed description, numerous specific details are set forth by way of example in order to provide a thorough understanding of the relevant disclosure. However, it will be apparent to those skilled in the art that this specification may be practiced without these details. In other instances, well-known methods, processes, systems, components, and / or circuits have been described at a higher level to avoid unnecessarily obscuring various aspects of this application. Various modifications to the disclosed embodiments will be apparent to those skilled in the art, and the general principles defined herein can be applied to other embodiments and applications without departing from the spirit and scope of this specification. Therefore, this specification is not limited to the embodiments shown, but is accorded the widest scope consistent with the claims.

[0075] The terminology used in this specification is for describing particular exemplary embodiments only and is not intended to be limiting. As used herein, the singular forms “a,” “an,” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising” and / or “including”, as used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not exclude the possibility of the presence and addition of at least one other feature, integer, step, operation, element, component, and / or combination thereof.

[0076] It should be understood that the terms “system,” “device,” “unit,” and / or “module” used herein are one way to distinguish different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0077] It should be understood that when a unit, engine, module, or block is referred to as being "in," "connected to," or "coupled to" another unit, engine, module, or block, it may be directly in connection with or coupled to the other unit, engine, module, or block, or communicate with other units, engines, modules, or blocks, or there may be intermediate units, engines, modules, or blocks, unless the context clearly indicates otherwise. As used in this specification, the term "and / or" includes any and all combinations of at least one of the related listed items.

[0078] It should be understood that although the terms "first," "second," "third," "fourth," etc., may be used herein to describe various elements, these elements should not be limited to these terms, which are only used to distinguish one element from another. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element, without departing from the scope of exemplary embodiments of the present invention.

[0079] Spatial and functional relationships between elements (e.g., between crystal elements) can be described using various terms, including “connection,” “engagement,” “interface,” and “coupling.” Unless explicitly described as “direct,” when describing a relationship between first and second elements in this disclosure, the relationship includes a direct relationship where no other intervening element is present between the first and second elements, and an indirect relationship where one or more intervening elements (spatial or functional) exist between the first and second elements. In contrast, when one element is described as being “directly connected,” engaged, interfaced, or coupled” to another element, there is no intermediate element present. Other terms used to describe relationships between elements should also be interpreted similarly (e.g., “between” vs. “directly between,” “adjacent” vs. “directly adjacent,” etc.). In this application, the term “and / or” may include any one or more of the related listed items or a combination thereof.

[0080] The anatomical structures shown in an image of a subject (e.g., a patient) may correspond to actual anatomical structures present within or on the subject's body. In this disclosure, the terms "object" and "subject" are used interchangeably to refer to a biological object (e.g., a patient, an animal) or a non-biological object (e.g., a phantom). In some embodiments, an object may include specific parts, organs, and / or tissues of an object. For example, an object may include a patient's head, bladder, brain, neck, torso, shoulder, arm, chest, heart, stomach, blood vessels, soft tissue, knee, foot, or similar parts, or any combination thereof.

[0081] The features and characteristics of this specification, as well as the operation and function of the related structural elements, and the economic efficiency of the combination and manufacture of the components, will become more apparent upon consideration of the following description. All accompanying drawings form part of this specification. However, it should be clearly understood that the drawings are for illustrative and descriptive purposes only and are not intended to limit the scope of this specification. It should be understood that the drawings are not drawn to scale.

[0082] Traditional hospital management systems typically require the deployment of systems for multiple different departments (e.g., surgical systems, emergency systems). The hospital management system described in some embodiments of this specification integrates and oversees these multiple departmental systems through a management space application. Specifically, the hospital management system described in this specification provides unified management of hospital resources. On one hand, through high integration and visualization, it enables the monitoring and optimization of healthcare services and the allocation of specific resources, thereby supporting various hospital management personnel and promoting refined hospital operations. On the other hand, for hospital-level management personnel, the system also provides data analysis and interactive visualization tools for decision-making, thereby enhancing the ability to comprehensively monitor and manage clinical operations (including outpatient services, surgery, and inpatient care). Furthermore, unified resource management can significantly improve the efficiency of medical resource utilization, reduce reliance on discrete, siloed information systems, and simplify hospital operations and management.

[0083] Specifically, a hospital management system may include an interface for users to manage hospital resources. In some embodiments, resources may include digital twins. A digital twin can map the state of an associated physical entity and is generated based on a preset data structure. A digital twin can be created using data from sensors and other sources to simulate the corresponding entity in the real world in real time. According to some embodiments of the hospital management system provided in this specification, digital twins can be used to monitor, analyze, simulate, control, and provide valuable analytics, thereby optimizing the performance of the hospital management system and improving its overall efficiency. In some embodiments, resources may include the hospital's digital intelligence resources. Digital intelligence resources may include intelligent agents, wherein intelligent agents include software entities generated based on artificial intelligence technology. In some embodiments of this specification, by customizing the configuration of intelligent agents in the hospital, the accuracy and efficiency of diagnosis and treatment can be significantly improved, while also enhancing the patient's treatment experience.

[0084] Figure 1 This is a block diagram of an exemplary medical service system 100 according to some embodiments of this application.

[0085] The Medical Service System 100, also known as the Meta-Hospital System, is built upon a variety of innovative technologies, including metaverse technology, XR technology (e.g., augmented reality (AR), virtual reality (VR), mixed reality (MR), etc.), AI technology, digital twin technology, IoT technology, data circulation technology (e.g., blockchain technology, data privacy computing technology), spatial computing technology, and image rendering technology.

[0086] like Figure 1 As shown, the medical service system 100 may include a physical hospital 110, a virtual hospital 130, a user space application 120, and a hospital support platform 140. In some embodiments, the hospital support platform 140 may map data related to the physical hospital 110 to the virtual hospital 130 corresponding to the physical hospital 110, and provide user services to relevant users of the physical hospital 110 through the user space application 120.

[0087] A physical hospital (110) refers to a hospital that exists in the physical world and has tangible attributes. In this article, healthcare institutions that provide medical, surgical, and psychiatric care and treatment to people are collectively referred to as hospitals.

[0088] like Figure 1 As shown, a physical hospital 110 may include multiple physical entities. For example, multiple physical entities may include departments, users, hardware equipment, user services, public areas, medical service processes, etc., or any combination thereof.

[0089] A department is a specialized unit or department that provides a particular type of medical care, treatment, and services. Each department may focus on a specific area of ​​medicine and may be staffed with healthcare professionals who have expertise in that area. For example, a department may include outpatient departments, inpatient departments, surgical departments, support departments (e.g., registration departments, pharmacy departments), internal medicine, surgery, specialty medicine, pediatric health care, etc., or any combination thereof.

[0090] Users can include any user associated with Physical Hospital 110 (or referred to as a user related to Physical Hospital 110). For example, users can include patients (or parts of patients, such as organs), companions, visitors to patients, hospital staff of Physical Hospital 110, suppliers of Physical Hospital 110, application developers of Physical Hospital 110, etc., or any combination thereof. Hospital staff of Physical Hospital 110 can include healthcare providers (e.g., doctors, nurses, technicians, etc.), hospital administrators, support staff, or similar personnel, or any combination thereof. Exemplary hospital administrators can include ward nursing administrators, clinical administrators, ward directors, hospital directors, hospital administrators, functional administrators, or similar personnel, or any combination thereof.

[0091] The hardware devices may include hardware devices located in the physical hospital 110 and / or hardware devices communicating with hardware devices in the physical hospital 110. Exemplary hardware devices may include terminal devices, medical service devices, sensing devices, infrastructure devices, etc., or any combination thereof.

[0092] Terminal devices may include terminal devices that interact with users of the healthcare service system 100. For example, terminal devices may include terminal devices that interact with patients (also called patient terminals), terminal devices that interact with doctors (also called doctor terminals), terminal equipment that interacts with nurses (also called nurse terminals), terminal devices that interact with remote visitors (also called remote terminal devices), or public terminals in the hospital (e.g., clinic terminals, bedside terminal devices, terminal devices in waiting areas, smart surgical terminals), etc., or any combination thereof. In this application, unless clearly obtained from the context or otherwise specified, terminal devices owned by the user and terminal devices provided to the user by the physical hospital 110 will be collectively referred to as user terminal devices or user-interacting terminal devices.

[0093] Terminal devices may include mobile terminals, XR devices, smart wearable devices, etc. Mobile terminals may include smartphones, personal digital assistants (PDAs), displays, gaming devices, navigation devices, handheld terminals (POS), tablets, etc., or any combination thereof.

[0094] XR devices may include devices that allow users to participate in extended reality experiences. For example, XR devices may include VR components, AR components, MR components, etc., or any combination thereof. In some embodiments, XR devices may include XR headsets, XR glasses, XR patches, stereo headphones, etc., or any combination thereof. For example, XR devices may include Google Glass™, Oculus Rift™, Gear VR™, Apple Vision Pro™, etc. Specifically, XR devices may include display components on which virtual content can be rendered and / or displayed. In some embodiments, XR devices may further include input components. The input components enable user interaction between the user and the virtual content (e.g., a virtual surgical environment) displayed on the display components. For example, the input components may include touch sensors, microphones, image sensors, etc., configured to receive user input, which can be provided to the XR device and used to control the virtual world by changing the visual content presented on the display components. Input components may include controllers, gloves, styluses, consoles, etc.

[0095] Smart wearable devices may include smart bracelets, smart shoes and socks, smart glasses, smart helmets, smartwatches, smart clothing, smart backpacks, smart accessories, and any combination thereof. In some embodiments, smart wearable devices may acquire a user's physiological data (e.g., heart rate, blood pressure, body temperature, etc.).

[0096] Medical service equipment can be configured to provide medical services to patients. For example, medical service equipment may include examination equipment, nursing equipment, treatment equipment, or any combination thereof.

[0097] The examination equipment can be configured to provide examination services to patients, such as collecting patient examination data. Exemplary examination data may include heart rate, respiratory rate, body temperature, blood pressure, medical imaging data, fluid test reports (e.g., blood test reports), or any combination thereof. Accordingly, the examination equipment may include vital sign monitors (e.g., blood pressure monitors, blood glucose meters, heart rate monitors, thermometers, digital stethoscopes, etc.), medical imaging equipment (e.g., computed tomography (CT) equipment, digital subtraction angiography (DSA) equipment, magnetic resonance (MR) equipment, etc.), laboratory equipment (e.g., routine blood test equipment, etc.) or any combination thereof.

[0098] Nursing devices can be configured to provide nursing services to patients and / or assist healthcare providers in providing nursing services. Exemplary nursing devices may include hospital beds, patient care robots, smart nursing carts, smart medicine boxes, smart wheelchairs, etc.

[0099] Treatment devices can be configured to provide treatment services to patients and / or assist healthcare providers in providing treatment services. Exemplary treatment devices may include surgical equipment, radiation therapy equipment, physical therapy equipment, etc., or any combination thereof.

[0100] Sensing devices can be configured to acquire sensory information related to their environment. For example, sensing devices may include image sensors, sound sensors, etc. Image sensors can be configured to acquire image data in the physical hospital 110, and sound sensors can be configured to acquire voice signals in the physical hospital 110. In some embodiments, the sensing device can be a standalone device or integrated into another device. For example, a sound sensor can be part of a medical service device or terminal device.

[0101] Basic infrastructure can be configured to support data transmission, storage, and processing. For example, basic infrastructure may include networks, data center facilities, computing devices, computing chips, storage devices, etc.

[0102] In some embodiments, at least a portion of the hardware of the physical hospital 110 is an IoT device. An IoT device is a device with sensors, processing capabilities, software, and other technologies that connects to and exchanges data with other devices and systems via the internet or other communication networks. For example, one or more medical service devices and / or sensing devices of the physical hospital 110 are IoT devices and are configured to transmit collected data to the hospital support platform 140 for storage and / or processing.

[0103] User services may include any services provided to users by the hospital support platform 140. For example, user services may include medical services provided to patients and / or accompanying persons, support services provided to staff and / or suppliers of the physical hospital 110, etc. In some embodiments, user services may be provided to patients, doctors, and hospital administrators through the user space application 120, which will be described in detail below.

[0104] Public areas refer to shared spaces accessible to users (or some users) within a physical hospital 110. For example, public areas may include reception areas (e.g., front desk), waiting areas, and corridors, or any combination thereof.

[0105] A medical service process refers to the procedure by which corresponding medical services are provided to a patient. A medical service process typically includes several steps and / or stages through which a user must go to obtain the corresponding medical service. Exemplary medical service processes may include outpatient processes, inpatient processes, surgical processes, or similar processes, or any combination thereof. In some embodiments, a medical service process may include medical service processes corresponding to different departments, different diseases, etc. In some embodiments, a preset data collection protocol can be set, specifying the standard steps involved in the medical service process and how to collect data related to the medical service process.

[0106] User space application 120 provides users with access to user services provided by hospital support platform 140. User space application 120 can be an application, plugin, website, app, or any other suitable form. For example, user space application 120 is an application installed on a user's terminal device, which includes a user interface for users to initiate requests and receive corresponding services.

[0107] In some embodiments, the user space application 120 may include different applications corresponding to different types of users. For example, the user space application 120 may include a patient space application corresponding to a patient, a medical space application corresponding to a doctor, a management space application corresponding to an administrator, or any combination thereof. The user services provided through the patient space application, medical space application, and management space application are also referred to as patient space services, medical space services, and management space services, respectively. Exemplary patient space services include registration services, route guidance services, pre-consultation services, remote consultation services, inpatient services, and discharge services. Exemplary medical space services include scheduling services, surgical planning services, surgical simulation services, patient management services, remote ward rounds services, and remote outpatient services. Exemplary administrator space services include monitoring services, medical service evaluation services, equipment parameter setting services, service parameter setting services, and resource scheduling services.

[0108] In some embodiments, the patient space application, medical space application, and management space application can be integrated into a single user space application 120, and the user space application 120 can be configured to provide access points for each type of user (e.g., patients, healthcare providers, administrators, etc.). As an example only, a specific user can have a corresponding account, which can be used to log in to the user space application, view relevant medical data, and obtain corresponding user services.

[0109] According to some embodiments of this application, by providing user space applications for different types of users, each type of user can easily obtain various user services that he / she may need on their respective user space application. Furthermore, currently users typically need to install various applications to obtain different user services, which leads to poor user experience and high development costs. Therefore, the user space application of this application can improve user experience, enhance service quality and efficiency, strengthen service security, and reduce development or operating costs.

[0110] In some embodiments, the user space application 120 can be configured to provide relevant users of the physical hospital 110 with an access point to interact with the virtual hospital 130. For example, through the user space application 120, users can enter instructions to retrieve digital content of the virtual hospital 130 (e.g., digital twin models of hardware devices, patient organs, and public areas), view digital content, and interact with digital content. As another example, through the user space application 120, users can communicate with virtual characters representing intelligent agents. In some embodiments, the hospital's public terminals can have a management space application installed, and administrator accounts for the corresponding departments of the public terminals can be logged into the management space application. Users can receive user services through the management space application installed on the public terminals.

[0111] Virtual hospital 130 is a digital twin (i.e., a virtual representation or virtual copy) of physical hospital 110, used to simulate, analyze, predict, and optimize the operational status of physical hospital 110. For example, virtual hospital 130 can be a real-time digital copy of physical hospital 110.

[0112] In some embodiments, digital technologies can be used to present the virtual hospital 130 to a user. For example, when a user interacts with the virtual hospital 130, XR technology can be used to present at least a portion of the virtual hospital 130 to the user. By way of example only, MR technology can be used to overlay at least a portion of the virtual hospital 130 onto the user's real-world view.

[0113] In some embodiments, the virtual hospital 130 may include digital twins of physical entities associated with the physical hospital 110. A digital twin is a virtual representation of a physical entity (e.g., a virtual copy, a mapping, a digital simulator). The digital twin can reflect and predict the state, behavior, and performance of the physical entity in real time. For example, the virtual hospital 130 may include digital twins of at least a portion of the physical hospital 110's medical services, departments, users, hardware equipment, user services, public areas, and medical service processes. Digital twins of physical entities can take various forms, including models, images, graphics, text, and numerical values. For example, a digital twin may be a virtual hospital corresponding to a physical hospital, virtual personnel (e.g., virtual doctors, virtual nurses, and virtual patients) corresponding to personnel entities (e.g., doctors, nurses, and patients), and virtual equipment (e.g., virtual imaging equipment and virtual scalpels) corresponding to medical service equipment (e.g., imaging equipment and scalpels).

[0114] In some embodiments, a digital twin may include one or more first digital twins and / or one or more second digital twins. The state of each first digital twin may be updated based on updates to the state of the corresponding physical entity. For example, in the process of mapping data associated with a physical hospital 110 to a virtual hospital 130, one or more first digital twins may be updated. One or more second digital twins may be updated through at least one of user-space applications 120, and an update to each second digital twin may result in an update to the state of the corresponding physical entity. In other words, when the state of the corresponding physical entity changes, the first digital twin may be updated accordingly; when the second digital twin is updated, the state of the corresponding physical entity also changes. For example, one or more first digital twins may include digital twins of public areas, medical services, users, hardware devices, etc., and one or more second digital twins may include digital twins of hardware devices, user services, medical service processes, etc. It should be understood that a digital twin may be either a first digital twin or a second digital twin.

[0115] According to some embodiments of this application, by generating a virtual hospital 130 that includes a digital twin of the physical entity associated with the physical hospital 110, the physical hospital 110 (including hardware devices, users, user services, medical service processes, etc.) can be simulated and tested in a safe and controlled environment. Through virtual-reality linkage (e.g., real-time interaction between the physical hospital 110 and the virtual hospital 130), various medical scenarios can be predicted and responded to more accurately, thereby improving the quality and efficiency of medical services. Furthermore, the application of XR technology and virtual reality integration technology makes the interaction of relevant users more natural and intuitive, providing a more comfortable and efficient medical environment, thereby enhancing the user experience.

[0116] In some embodiments, the virtual hospital 130 may further include an intelligent agent that can self-evolve based on data related to the physical hospital 110 and AI technology.

[0117] An intelligent agent is an agent that acts intelligently. For example, an intelligent agent can include a computing / software entity that can autonomously learn and evolve, and perceive and analyze data to perform specific tasks and / or achieve specific goals (e.g., healthcare service processes). Through AI technologies (e.g., reinforcement learning, deep learning, etc.), intelligent agents can continuously learn and self-optimize / evolve in their interactions with the environment. Furthermore, intelligent agents can collect and analyze massive amounts of data (e.g., data related to physical hospital 110) using big data technologies, and mine patterns and learn rules from the data to optimize decision-making processes, thereby identifying environmental changes in uncertain or dynamic environments, responding quickly, and making reasonable judgments. For example, an intelligent agent can autonomously learn and evolve based on AI technology to adapt to changes in physical hospital 110. As an example only, an intelligent agent can be built based on NLP technologies (e.g., large language models, etc.) and can automatically learn and autonomously update through large amounts of linguistic text (e.g., hospital business data and patient feedback information) to improve the quality of user services provided by physical hospital 110.

[0118] In some embodiments, intelligent agents may include different types of intelligent agents corresponding to different medical service processes, different user services, different departments, different diseases, different hospital positions (e.g., nurses, doctors, technicians, etc.), and different stages of medical service processes. Specific types of intelligent agents are used to handle tasks corresponding to their specific types. In some embodiments, an intelligent agent may correspond to different medical service processes (or different medical services, or different departments, or different diseases, or different hospital locations). In some embodiments, intelligent agents may operate by referring to basic configuration data (e.g., dictionaries, knowledge graphs, templates, etc.) corresponding to the department and / or disease of the intelligent agent. In some embodiments, multiple intelligent agents can collaborate and share information through network communication to jointly complete complex tasks.

[0119] In some embodiments, the configuration of the intelligent agent can be set. For example, basic configuration data used by the intelligent agent in operation can be set. Basic configuration data may include dictionaries, knowledge databases, templates, etc. Furthermore, the usage permissions of the intelligent agent can be set for different users. In some embodiments, the administrator of the physical hospital 110 can set the configuration of the intelligent agent through a management space application.

[0120] In some embodiments, the intelligent agent can be integrated into or deployed on a hardware device. For example, an intelligent agent corresponding to inpatient services can be integrated into a hospital bed or a presentation device for a hospital bed. In some embodiments, the intelligent agent can be integrated into or deployed on an embodied intelligent robot. An embodied intelligent robot is a robotic system that combines physical presence (manifestation) with intelligent behavior (cognition). Embodied intelligent robots can be configured to interact with the real world in a way that mimics or complements human capabilities, utilizing physical form and cognitive functions to perform tasks, make decisions, and adapt to the environment. By utilizing artificial intelligence and sensor technology, embodied intelligent robots can operate autonomously, interact with the environment, and continuously improve their performance. For example, an embodied intelligent robot can be configured with an intelligent agent corresponding to surgical services and assist doctors in performing surgery.

[0121] In some embodiments, at least a portion of user services can be provided based on intelligent agents. For example, at least a portion of user services can be provided to relevant users based on processing results, wherein the processing results are generated by at least one intelligent agent based on data related to the physical hospital 110. As an example only, the data related to the physical hospital 110 may include data related to the medical service processes of the physical hospital 110, the intelligent agents may include intelligent agents corresponding to the medical service processes, and user services can be provided to relevant users of the medical service processes by processing data using the intelligent agents corresponding to the medical service processes.

[0122] The hospital support platform 140 can be configured to provide technical support to the healthcare service system 100. For example, the hospital support platform 140 may include computing hardware and software to support innovative technologies, including XR technology, AI technology, digital twin technology, data flow technology, etc. In some embodiments, the hospital support platform 140 may include at least a storage device for data storage and a processing device for data computation.

[0123] In some embodiments, the hospital support platform 140 can support interaction between a physical hospital 110 and a virtual hospital 130. For example, the processing device of the hospital support platform 140 can acquire data related to the physical hospital 110 from hardware devices and map the data related to the physical hospital 110 into the virtual hospital 130. For example, the processing device of the hospital support platform 140 can update a portion of the digital twin in the virtual hospital 130 (e.g., one or more first digital twins) based on the acquired data, so that each portion of the digital twin in the virtual hospital 130 can reflect the updated status of the corresponding physical entity in the physical hospital 110. Based on this digital twin that is constantly updated with the corresponding physical entity, the user can understand the status of the physical entity related to the physical hospital 110 in real time, thereby enabling the monitoring and evaluation of the physical entity. As another example, the agent corresponding to the data related to the physical hospital 110 can be trained and / or updated based on the data related to the physical hospital 110, thereby self-evolving and self-learning.

[0124] In some embodiments, the hospital support platform 140 can support and / or provide user services to relevant users of the physical hospital 110. For example, in response to receiving a user service request from a user, the processing device of the hospital support platform 140 can provide the user service corresponding to the service request. Alternatively, in response to detecting that a user service needs to be provided to a user, the processing device of the hospital support platform 140 can control a physical or virtual entity corresponding to the user service to provide it. For example, in response to detecting that a patient has been admitted to a ward, the processing device of the hospital support platform 140 can control a smart nursing cart to guide a nurse to the ward to conduct admission examinations on the patient.

[0125] In some embodiments, at least some user services may be provided to the relevant user based on the interaction between the relevant user and the virtual hospital 130. Interaction refers to the interaction or influence (e.g., dialogue, behavior, etc.) between the relevant user and the virtual hospital 130. For example, the interaction between the relevant user and the virtual hospital 130 may include the interaction between the relevant user and a digital twin in the virtual hospital 130, the interaction between the relevant user and an intelligent agent, the interaction between the relevant user and a virtual character, or any combination thereof.

[0126] In some embodiments, at least a portion of user services can be provided to the relevant user based on the interaction between the relevant user and at least one of the digital twins. For example, an update instruction for the second digital twin input by the relevant user can be received through the user space application 120, and the corresponding physical entity of the second digital twin can be updated according to the update instruction. As another example, the user can view a first digital twin of a physical entity (e.g., a 3D digital twin model of a patient's organ or hardware device) through the user space application 120 to understand the state of the physical entity. Optionally, the user can change the display angle, display size, etc. of the digital twin.

[0127] In some embodiments, the processing device of the hospital support platform 140 can present a virtual character corresponding to the intelligent agent through a user space application, interact with relevant users, and provide at least a portion of user services to relevant users based on the interaction between relevant users and the virtual character.

[0128] In some embodiments, the hospital support platform 140 may have a five-layer structure, including a hardware device layer, an interface layer, a data processing layer, an application development layer, and a service layer, as can be seen in [reference needed]. Figure 3 And related descriptions. In some embodiments, the hardware of the physical hospital 110 may be part of the hospital support platform 140.

[0129] According to some embodiments of this application, a virtual hospital corresponding to the physical hospital can be established by comprehensively integrating various internal and external resources of the physical hospital (e.g., medical service equipment, hospital personnel, medicines, and consumables). This virtual hospital can reflect the real-time status (e.g., changes, updates, etc.) of the physical entities related to the physical hospital, thereby enabling the monitoring and evaluation of these physical entities. This integration can provide accurate data support for the operation and intelligent decision-making of healthcare services. Furthermore, through the virtual hospital, users related to healthcare services can jointly establish an open and shared ecosystem, thereby promoting innovation and improvement in healthcare services.

[0130] Furthermore, it can provide comprehensive patient healthcare services throughout the entire life cycle, linking both in-hospital and out-of-hospital care. The perspective of medical services expands from simple disease treatment to encompass the entire patient lifecycle, including prevention, diagnosis, treatment, rehabilitation, and health management. By establishing in-hospital and out-of-hospital collaboration, physical hospitals can better integrate online and offline resources to provide patients with comprehensive and continuous healthcare services. For example, through remote monitoring and online consultations, patients' health status can be followed up in real time, treatment plans can be adjusted promptly, and treatment outcomes improved.

[0131] Figure 2 This is a schematic diagram of an exemplary medical service system 200 according to some embodiments of this application.

[0132] like Figure 2 As shown, the healthcare service system 200 may include a processing device 210, a network 220, a storage device 230, one or more healthcare service devices 240, one or more sensing devices 250, one or more patient terminals 260 for a patient 261, and one or more doctor terminals 270 for a doctor 271 associated with the patient 261. In some embodiments, the components in the healthcare service system 200 may be interconnected and / or communicate with each other via wireless connections, wired connections, or a combination thereof. The connections between the components of the healthcare service system 200 may be variable.

[0133] Processing device 210 can process data and / or information obtained from storage device 230, medical service device 240, sensing device 250, patient terminal 260, and / or doctor terminal 270. For example, processing device 210 can map data related to a physical hospital to a virtual hospital corresponding to the physical hospital, and provide user services to patient 261 and doctor 271 respectively through patient terminal 260 and / or doctor terminal 270 by processing data related to the physical hospital. As another example, processing device 210 can maintain digital intelligent objects and provide user services to patient 261 and doctor 271 respectively through patient terminal 260 and / or doctor terminal 270 by involving digital intelligent objects in processing data related to the physical hospital.

[0134] In some embodiments, the processing device 210 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, the processing device 210 may be located locally or remotely within the healthcare service system 200. In some embodiments, the processing device 210 may be implemented on a cloud platform. For example, the cloud platform may include private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, inter-cloud cloud, multi-cloud, etc., or combinations thereof.

[0135] In some embodiments, processing device 210 may include one or more processors (e.g., a single-core processor or a multi-core processor). For illustrative purposes only, only one processing device 210 is described in the medical service system 200. However, it should be noted that the medical service system 200 of this application may also include multiple processing devices. Therefore, as in this application, the operations and / or method steps performed by one processing device 210 may also be performed jointly or individually by multiple processing devices.

[0136] Network 220 may include any suitable network capable of facilitating the exchange of information and / or data between the healthcare service system 200. Network 220 may be or include wired networks, wireless networks (e.g., 802.11 networks, Wi-Fi networks), Bluetooth™ networks, Near Field Communication (NFC) networks, and any combination thereof.

[0137] Storage device 230 may store data, instructions, and / or any other information. In some embodiments, storage device 230 may store data obtained from other components of the healthcare system 200. In some embodiments, storage device 230 may store data and / or instructions that processing device 210 may perform or be used to perform the exemplary methods described in this application.

[0138] In some embodiments, the data stored in storage device 230 may include multimodal data. Multimodal data may include data in various forms (e.g., images, graphics, videos, text, etc.), various types of data, data obtained from different sources, data related to different medical procedures (e.g., diagnosis, surgery, rehabilitation, etc.), and data related to different users (e.g., patients, medical staff, administrators, etc.). For example, the data stored in storage device 230 may include medical data of patient 261 reflecting the health status of patient 261. For example, medical data may include patient 261's electronic medical record. An electronic medical record is an electronic file that records various types of patient data (e.g., basic information, examination data, imaging data). For example, an electronic medical record may include three-dimensional models of multiple organs and / or tissues of patient 261.

[0139] In some embodiments, storage device 230 may include mass storage devices, removable storage devices, volatile read-write memory, read-only memory (ROM), etc., or any combination thereof. In some embodiments, storage device 230 may include data lakes and data warehouses, combining... Figure 3 Provide a detailed description.

[0140] Medical service equipment 240 can be used to provide or assist with medical services. For example... Figure 2 As shown, the medical service equipment 240 includes a consultation room terminal 240-1, a hospital bed 240-2, an intelligent surgical terminal 240-3, an intelligent nursing cart 240-4, an intelligent wheelchair 240-5, or any combination thereof.

[0141] Clinic terminal 240-1 refers to a terminal device configured in a clinic for use by doctors and patients during outpatient medical procedures. For example, clinic terminal 240-1 may include one or more of a screen, a sound output component, an image sensor, or a sound sensor. The screen of clinic terminal 240-1 may display a consultation interface, on which data may be displayed to facilitate communication between doctor and patient. Exemplary data may include electronic medical records (or portions thereof), pre-consultation records, medical images, 3D organ models, examination results, consultation suggestions, etc.

[0142] Hospital bed 240-2 refers to a bed in a ward that can support inpatients and provide user services to them. Hospital bed 240-2 may include a bed, bedside terminal equipment, bedside examination equipment, sensors, etc., or any combination thereof. Bedside terminal equipment may include XR equipment, display equipment, mobile devices, etc., or any combination thereof. In some embodiments, hospital bed 240-2 may be controlled by an intelligent agent corresponding to inpatient services, wherein the hospital bed may also be referred to as an intelligent hospital bed or a meta-hospital bed.

[0143] The intelligent surgical terminal 240-3 refers to a device configured with an intelligent agent for assisting surgery, and controlled by an intelligent agent corresponding to the surgical service. The intelligent surgical terminal 240-3 can sense interactions (e.g., dialogues, behaviors, etc.) between the healthcare provider, the patient, and the intelligent agent, and acquire data captured by the sensing device 250, thereby providing surgical assistance. In some embodiments, the intelligent surgical terminal 240-3 can be configured to perform risk warnings for surgical procedures, generate surgical records of the surgical process, etc., based on the intelligent agent configured therein.

[0144] The intelligent nursing cart 240-4 refers to a nursing cart with automatic driving capabilities that can assist in patient treatment and care. For example, the intelligent nursing cart 240-4 can be configured to guide nurses to wards to conduct admission examinations for patients. In some embodiments, the intelligent nursing cart can be controlled by an intelligent agent (e.g., an intelligent agent corresponding to inpatient services, a nursing intelligent agent). In some embodiments, the intelligent nursing cart 240-4 may include a trolley, a presentation device, one or more examination devices and / or nursing tools, sensing devices (such as image sensors, GPS sensors, sound sensors, etc.), etc. In some embodiments, the intelligent nursing cart 240-4 can be configured to acquire relevant treatment and care information of the patient and generate physical examination data, nursing data, etc. Physical examination data may include the patient's vital signs data. Nursing data may include detailed records of nursing operations, such as nursing time, nursing operator, nursing measures, patient responses, etc.

[0145] The intelligent wheelchair 240-5 refers to a transportation device for intelligent patient transport. In some embodiments, the intelligent wheelchair 240-5 can be configured to perform autonomous navigation through integrated sensors and maps, locate the patient's position using radio frequency identification (RFID), Bluetooth, or Wi-Fi signals, and identify the patient through biometric technology. In some embodiments, the intelligent wheelchair 240-5 can be controlled by an intelligent agent (e.g., an intelligent agent corresponding to inpatient services, an intelligent agent corresponding to surgical services). In some embodiments, the intelligent wheelchair 240-5 can be configured to generate data (e.g., a record of the interaction content between the intelligent agent and the patient) by sensing interaction data through a built-in camera / sensor.

[0146] The sensing device 250 can be configured to collect sensing information related to its environment. In some embodiments, the sensing device 250 may include sensing devices in the physical hospital 110. For example, the sensing device 250 may include an image sensor 250-1, a sound sensor 250-2, a temperature sensor, a humidity sensor, etc.

[0147] Patient terminal 260 can be a terminal device that interacts with patient 261. In some embodiments, patient terminal 260 may include mobile terminal 260-1, XR device 260-2, smart wearable device 260-3, etc. Doctor terminal 270 can be a terminal device that interacts with doctor 271. In some embodiments, doctor terminal 270 may include mobile terminal 270-1, XR device 270-2, etc. In some embodiments, patient 261 can access user space applications (e.g., patient space applications) through patient terminal 260, and doctor 271 can access user space applications (e.g., medical space applications) through doctor terminal 270. In some embodiments, patient 261 and doctor 271 can communicate remotely with each other through patient terminal 260 and doctor terminal 270 to provide telemedicine services, such as remote outpatient services, remote ward rounds, remote follow-up services, etc.

[0148] Sensing device 250, patient terminal 260, and doctor terminal 270 can be configured as data sources to provide information to healthcare service system 200. For example, these devices can transmit the collected data to processing device 210, and processing device 210 can provide user services based on the received data.

[0149] It should be noted that the descriptions of the healthcare service systems 100 and 200 above are illustrative and not intended to limit the scope of this application. Many alternatives, modifications, and variations will be apparent to those skilled in the art. The features, structures, methods, and other features of the exemplary embodiments herein can be combined in various ways to obtain additional and / or optional exemplary embodiments. For example, healthcare service system 200 may include one or more additional components, such as terminal devices for other users, public terminal devices in the hospital, etc. As another example, two or more components of healthcare service system 200 may be integrated into a single component.

[0150] Figure 3 This is a schematic diagram of an exemplary hospital support platform 300 according to some embodiments of this application.

[0151] like Figure 3As shown, the hospital support platform 300 may include a hardware layer 310 (also called a hardware module), an interface layer 320 (also called an interface module), a data processing layer 330 (also called a data processing module), an application development layer 340 (also called an application development module), and a service layer 350 (also called a service module). It should be understood that the terms "layer" and "module" in this application are only used for logically dividing the components of the hospital support platform and are not intended to be limiting.

[0152] Hardware layer 310 can be configured to provide the hardware foundation for interaction between the real world and the digital world, and may include one or more hardware devices related to hospital operations. Exemplary hardware devices may include medical service devices, sensing devices, terminal devices, and infrastructure devices.

[0153] Interface layer 320 can be connected to hardware layer 310 and data processing layer 330. Interface layer 320 can be configured to acquire data collected by hardware devices of hardware layer 310 and send the data to data processing layer 330 for storage and / or processing. Interface layer 320 can also be configured to control at least a portion of hardware devices of hardware layer 310. In some embodiments, interface layer 320 may include hardware interfaces and software interfaces (e.g., data interfaces, control interfaces).

[0154] The data processing layer 330 can be configured to store and / or process data. The data processing layer 330 may include a processing device on which multiple data processing units can be configured. The data processing layer 330 can be configured to acquire data from the interface layer 320 and process the data through at least one data processing unit to provide user services related to hospital operations.

[0155] The data processing unit may include various preset algorithms for implementing data processing. In some embodiments, the data processing layer 330 may include a processing device (e.g., Figure 2 The data processing unit can be configured on the processing device (processing device 210). In some embodiments, the data processing unit may include an XR unit configured to process data using XR technology to implement XR services, an AI unit (e.g., an intelligent agent unit) configured to process data using AI technology to implement AI services, a digital twin unit configured to process data using digital twin technology to implement digital twin services, and a data circulation unit configured to process data using data circulation technologies (e.g., blockchain technology, data privacy computing technology) to implement data circulation services, etc.

[0156] In some embodiments, the data processing layer 330 may further include a data center configured to store data. In some embodiments, the data center may employ a lake warehouse integrated architecture, which may include a data lake and a data warehouse. The data lake may be used to persistently store large amounts of data in a tamper-proof manner. The data warehouse may be used to store index data corresponding to the data in the data lake. The data stored in the data lake may include native (or raw) data collected by hardware devices, derived data generated based on native data, etc. In some embodiments, the data in the data lake may be processed by a processing device (e.g., processing device 210).

[0157] The application development layer 340 can be configured to support application development, publishing, and subscription. The application development layer 340 is also referred to as the ecosystem suite layer. In some embodiments, the application development layer 340 can be configured to provide application developers with open interfaces to access or invoke at least a portion of the data processing units and utilize at least a portion of the data processing units to develop applications. In some embodiments, such as... Figure 3 As shown, the application development layer 340 can provide development toolkits, application marketplaces, multi-tenant operation platforms, cloud official websites, workspaces, and other support toolkits to assist developers in their work.

[0158] Service layer 350 can be configured so that users related to hospital business can access user services related to hospital business through user space applications.

[0159] This application provides a hospital support platform designed for the comprehensive management of various resources within a hospital, including hardware, software, and data resources. In some embodiments, the platform further integrates data processing units capable of supporting advanced technologies such as artificial intelligence, XR, digital twins, and blockchain. These advanced technologies are used to improve the efficiency and quality of services in the healthcare industry. For example, artificial intelligence technology enables the autonomous evolution and continuous optimization of hospital operations, while XR and digital twin technologies facilitate the creation and maintenance of virtual hospitals. These virtual hospitals can interact with users, providing immersive and novel service experiences. Furthermore, the platform includes an application development layer that grants access to these advanced technologies to third-party developers in the healthcare industry. This access fosters an open ecosystem, promoting application development and innovation, thereby driving advancements in healthcare services.

[0160] Figure 4 This is a schematic diagram of a hospital management system 400 according to some embodiments of this specification. For example... Figure 4 As shown, the hospital management system 400 may include users 410, interface 420, and hospital resources 430.

[0161] User 410 can manage hospital resources 430 through interface 420. User 410 may include hospital administrators, such as the hospital director, heads of hospital departments (e.g., dentistry, internal medicine, etc.), head nurses of hospital departments, etc. Hospital resources 430 may include equipment, personnel, digital twins, digital resources (e.g., intelligent agents), etc., or any combination thereof. In some embodiments, different users 410 may have different management permissions for different resources 430. In some embodiments, a specific user 410 only manages specific resources 430. For example, the hospital director can manage all hospital resources 430. The head of the dentistry department only manages resources 430 related to the dentistry department.

[0162] Interface 420 may be presented by the display screen of the administrator terminal device. The display screen may include a light-emitting diode (LED) display screen, a liquid crystal display screen, an electronic ink display screen, a touch liquid crystal display screen, an organic LED touch screen, or similar devices, or any combination thereof. The terminal device may include a mobile device, an XR device, a smart wearable device, etc. In some embodiments, interface 420 may be an interface presented by a management space application. Further descriptions of the terminal device and management space application can be found in other parts of this specification, such as... Figure 1 And related explanations.

[0163] In some embodiments, interface 420 is configured to present a virtual avatar to assist user 410 in managing resources. A virtual avatar is a digital representation of a human or other entity, created through computer graphics and artificial intelligence. The virtual avatar can be configured to interact with user 410. Interface 420 can also be configured to present interface elements to facilitate user 410 initiating a conversation with the virtual avatar.

[0164] In some embodiments, user 410 can initiate a conversation with a virtual character through interface elements, expressing their resource management requirements (e.g., viewing information related to a specific type of resource, scheduling a specific type of resource, updating relevant parameters of a specific type of resource, etc.) through voice, text, gestures, etc. The processing device (e.g., processing device 220) can analyze the user's input (e.g., using artificial intelligence technology, using an intelligent agent), determine feedback information, and convey the feedback information to user 410 through the virtual character during the conversation. In some embodiments, the content displayed through interface 420 can be updated based on the content of the conversation.

[0165] For example only, Figure 5 This is a schematic diagram of interface 420 according to some embodiments of this specification. For example... Figure 5As shown, interface 420 may include a search area 421 and a results display area 422. Search area 421 can be used to search for information when managing resources 430. In some embodiments, search area 421 may present a search box for inputting information (e.g., text information). In some embodiments, search area 421 may present a virtual character 4221. Virtual character 4221 can interact with user 410; for example, virtual character 4221 can simulate human language expression, gestures, etc., to provide user 410 with a realistic interactive experience. Search area 421 can present interface elements 4222 to user 410 for initiating a conversation with virtual character 4221. User 410 can interact with virtual character 4221 using natural language via voice or text.

[0166] The results show that area 422 can be configured to present information, such as feedback information provided to user 410 during a session. For example, as... Figure 5 As shown, the content of the conversation between user 410 and virtual character 4221 can represent the data that user 410 needs to obtain related to the inpatient ward. The results display area 422 can automatically present a digital twin view corresponding to the inpatient ward and inpatient operation data analysis results.

[0167] In some embodiments, the content displayed in the results display area 422 can be updated based on information entered into the search box. In some embodiments, the content displayed in the results display area 422 can be updated based on the content of the session. In some embodiments, such as Figure 5 As shown, the search area 421 and the results display area 422 can be displayed simultaneously on the interface 420. Alternatively, the search area 421 and the results display area 422 can be displayed separately on the interface 420. For example, when user 410 queries information, the interface 420 only displays the search area 421. After the query is completed, the interface 420 only displays the results display area 422.

[0168] In some embodiments, interface 420 may also present interface elements corresponding to commonly used services. Since different users 410 have access to different information, the interface elements presented to different users 410 may be different.

[0169] In some embodiments of this specification, the interface of a traditional hospital management system is limited to providing users with predefined analysis results. The interface of the hospital management system described in this specification enables users to retrieve data across various dimensions. Furthermore, the introduction of virtual avatars allows users to express their needs using natural language, thereby enhancing the user experience and improving the quality and efficiency of resource management services.

[0170] In some embodiments, such as Figure 4As shown, the hospital's resource 430 includes a digital twin 431. The digital twin maps the state of an associated physical entity and can be generated according to a preset data structure. An associated physical entity refers to the physical entity that corresponds to the data twin. In this specification, a digital twin refers to a virtual representation (or digital copy) of a physical entity. A physical entity refers to any object or thing existing in the physical world that can be directly or indirectly observed, measured, or interacted with. In some embodiments, such as... Figure 4 As shown, the physical entity corresponding to the digital twin 431 may include user services (e.g., medical services), users, hardware devices (e.g., medical service equipment, sensing devices), public areas, hospital medical service processes (e.g., consultation process, hospitalization process, surgical process), etc., or any combination thereof. Users may include patients or parts thereof (e.g., organs), medical service providers (e.g., doctors, nurses), etc.

[0171] In some embodiments, the preset data structure of the digital twin can specify the format of the digital twin, the type of information reflected by the digital twin, the storage address of the digital twin, the access permissions of the digital twin, the update mode of the digital twin, the modification permissions of the digital twin, the modification permissions of the preset data structure, etc., or any combination thereof. In some embodiments, the preset data structure can be a default data structure provided by the hospital or a data structure customized by the user 410 through the interface 420.

[0172] A digital twin corresponding to an associated physical entity can be represented in any form that accurately represents the physical entity, such as a model, image, text, or digital data (e.g., parameters). For example, a digital twin corresponding to a patient's organ can be represented using a 3D model of that organ. As another example, a digital twin corresponding to a display device can be represented using various parameters of the display device.

[0173] In some embodiments, digital twin 431 may include one or more first digital twins. For each first digital twin, mapping the state of the associated physical entity may include updating the first digital twin based on the state update of the associated physical entity. For example, the first digital twin may include a digital twin corresponding to a hospital public area, a digital twin corresponding to medical services, a digital twin corresponding to a user (e.g., a patient, a patient's organ, a doctor), a digital twin corresponding to hospital hardware equipment, etc.

[0174] In some embodiments, a digital twin may include one or more second digital twins. For each second digital twin, the state of the mapped associated physical entity may include updating the associated physical entity based on updates to the second digital twin. Exemplary second digital twins may include digital twins corresponding to hardware devices, digital twins corresponding to user services, digital twins corresponding to healthcare service processes, or similar digital twins.

[0175] In some embodiments, a user can interact with the virtual character 4221 (e.g., have a conversation) to access the first and second digital twins for viewing and / or updating the second digital twin. It should be understood that a digital twin can simultaneously serve as both the first and second digital twin. Further descriptions of digital twins can be found in other parts of this specification (e.g., Figure 6 (and its description).

[0176] In some embodiments, user 410 can manage digital twin 431 through interface 420. Since digital twins can reflect the state of associated physical entities, the physical entities of the hospital can be managed by managing digital twin 431. For example, user 410 can view the first digital twin corresponding to a physical entity (e.g., a 3D digital twin model of a patient's organ or hardware device, or a digital twin view of a public area) through interface 420 to understand and assess the state of the physical entity. The user can choose to change the display angle, display size, etc., of the displayed first digital twin. Exemplary digital twins displayed on interface 420 can be as follows: Figures 7A-7F or Figures 8A-8F As shown. As another example, user 410 can input update instructions for the second digital twin through interface 420 to update the state of the associated physical entity.

[0177] In some embodiments, hospital resources 430 include the hospital's digital resources. Digital resources may include various types of digital assets and tools enhanced by artificial intelligence (AI) to support and improve digital operations, learning, and management, etc.

[0178] In some embodiments, such as Figure 4 As shown, digital intelligence resources may include intelligent agents 432. As used herein, an intelligent agent refers to an agent that performs tasks on behalf of a user with a certain degree of autonomy and intelligence.

[0179] In some embodiments, the intelligent agent may include a software entity that is built and implements self-evolution / optimization based on artificial intelligence technology, which may be configured on and implemented / executed by a processing device. Exemplary artificial intelligence technologies include machine learning algorithms (e.g., supervised learning algorithms, reinforcement learning algorithms, etc.), deep learning algorithms (e.g., neural network algorithms, etc.), evolutionary algorithms, ensemble learning algorithms, or similar algorithms or any combination thereof. In some embodiments, at least a portion of the intelligent agent may be further built based on natural language processing algorithms. Exemplary natural language processing algorithms may include language modeling algorithms, text preprocessing algorithms, text classification and sentiment analysis algorithms, sequence tagging algorithms, named entity recognition (NER) algorithms, machine translation algorithms, etc., or any combination thereof. For example, the intelligent agent may be represented by a virtual character, with which the user can interact via voice, text, gestures, etc. Therefore, the intelligent agent is built based on natural language processing algorithms to understand and analyze the user's input information, thereby determining feedback information and conveying the feedback information to the user through the virtual character.

[0180] In some embodiments, an intelligent agent may include a physical entity that further includes a software entity; an intelligent agent that includes both a software entity and a physical entity may also be referred to as an embodied intelligent agent. As used herein, an embodied intelligent agent is an intelligent agent capable of interacting with and adapting to its environment using its physical entity and sensorimotor capabilities. The physical entity of an embodied intelligent agent may include physical components such as processing devices, storage devices, sensors, robotic arms, actuators, and user interfaces. The software entity of an embodied intelligent agent may control some of the physical components to provide user services. For example, nursing equipment in a hospital may include embodied intelligent agents, such as patient care robots, intelligent nursing carts, etc. Patient care robots may include sensors, robotic arms, actuators, user interfaces, etc., or any combination thereof. The nursing agent on the patient care robot may control the physical entity to provide nursing services, such as assisting the patient to drink water, eat, or take medication. Intelligent nursing carts may have autonomous driving capabilities and be able to move to different locations in the hospital. For example, an intelligent nursing cart may be configured to guide nurses to wards to perform examinations or nursing procedures on patients. As another example, an intelligent nursing cart may be configured to present guidance information to guide nurses in performing examinations or nursing procedures. Optionally, the intelligent nursing cart may include one or more examination devices and / or nursing tools for nurses to use in performing examinations and / or nursing procedures.

[0181] In some embodiments, user 410 can manage agent 432 through interface 420. For example, user 410 can query and update information related to agent through interface 420. Since agent 432 can be used to participate in data processing to provide user services, user services can be managed by managing agent 432.

[0182] In some embodiments, interface 420 may present basic configuration data used by at least a portion of the agents. User 410 can update the basic configuration data through interface 420. The basic configuration data includes key information relied upon by the agent when providing specific services. Exemplary basic configuration data may include at least one of a dictionary (e.g., a word list, a personnel directory), a knowledge database, or a template. For example, for an agent used for outpatient registration, the basic configuration data may include a hospital department dictionary, a personnel dictionary of doctors in each department of the hospital, etc. As another example, for an agent used for online consultation services, the basic configuration data may include consultation report templates, etc. In some embodiments, the knowledge database may include a knowledge graph. In some embodiments, the knowledge database may include specifications for the department corresponding to the agent, such as disease description specifications, diagnostic specifications, prescription specifications, and medical order specifications.

[0183] In some embodiments, interface 420 may present at least a subset of operational metrics for the agent. Operational metrics may reflect information related to the quantity and quality of services provided by the agent. These operational metrics may include the number of users served by the agent, the number of services provided by the agent, the amount of data processed by the agent, the quality of the agent's services, or any combination thereof.

[0184] For example, Figure 11 This is an exemplary interface 420 for presenting information related to an intelligent agent, as shown in some embodiments of this specification. For example... Figure 11 As shown, the interface 420 may include a first display area 423 and a second display area 424. The first display area 423 can be configured to display basic configuration data used by the agent. The basic configuration data includes a dictionary, knowledge database, templates, etc. The user 410 can update the basic configuration data through the first display area 423 to adjust the agent. For example, for an agent used for online consultation services, the user 410 can modify the consultation report template to instruct the agent to output a consultation report based on the modified template. The second display area 424 is configured to display the agent's operational metrics. The agent's operational metrics include the number of users served by the agent, the number of services provided by the agent, the amount of data processed by the agent, and the service quality of the agent. In some embodiments, such as Figure 11 As shown, the first display area 423 and the second display area 424 can be displayed simultaneously on the interface 420. Alternatively, the first display area 423 and the second display area 424 can be displayed separately on the interface 420.

[0185] In some embodiments, the intelligent agent includes intelligent agents corresponding to different types of healthcare service providers. The intelligent agent corresponding to a healthcare service provider can replace or assist the healthcare service provider in performing tasks. For example, the intelligent agent corresponding to a doctor can replace or assist the doctor in providing consultation services. Healthcare service providers may include doctors, nurses, etc.

[0186] For example, an exemplary intelligent agent corresponding to a doctor can be shown in Table 1 below.

[0187] Table 1. Exemplary intelligent agents corresponding to doctors

[0188]

[0189]

[0190] Intelligent agents can interact with users through corresponding terminal devices. For example, an intelligent agent can receive user input through a terminal device and provide feedback for the terminal device to display. In some embodiments, the intelligent agent can be represented as a virtual digital character on the corresponding terminal device to communicate with the user.

[0191] As another example, an exemplary intelligent agent corresponding to a nurse can be shown in Table 2 below.

[0192] Table 2. Exemplary intelligent agents corresponding to nurses

[0193]

[0194] In some embodiments, the intelligent agent may include an intelligent agent corresponding to different hospital departments. Hospital departments may include any department within a hospital, such as the emergency department, internal medicine department, dental department, etc. The intelligent agent corresponding to a hospital department may be configured to perform tasks related to that hospital department.

[0195] In some embodiments, the intelligent agent may include intelligent agents corresponding to different medical service processes. For example, it may include at least one of a consultation intelligent agent, an inpatient intelligent agent, or a surgical intelligent agent. The intelligent agent corresponding to the medical service process may be configured to perform tasks related to the medical service process. For example, the intelligent agent corresponding to the medical service process may be configured to monitor updates of patient-related data after the medical service process. For further description of monitoring updates of patient-related data through intelligent agents corresponding to medical service processes, please refer to other parts of this specification (e.g., Figure 12 (and its description).

[0196] In some embodiments, the intelligent agent may include intelligent agents corresponding to different user services. User services may include user services provided to patients, user services provided to doctors, etc. In some embodiments, user services may be related to different stages of different medical service processes. In some embodiments, user services provided to patients can be obtained through a patient space application installed on the patient's terminal. User services provided to doctors can be obtained through a medical space application on the doctor's terminal. The intelligent agent corresponding to the user service may be configured to perform tasks related to the user service. For example, the user service may be related to a certain stage in the medical service process, and the intelligent agent corresponding to the user service may be configured to process data related to the patient in that stage of the medical service process, and provide user services to the relevant users in that stage based on the data processing results. Further descriptions of providing user services to users through the intelligent agent corresponding to the user service based on patient-related data can be found elsewhere in this specification (e.g., Figure 13 (and its description).

[0197] In some embodiments, different training data and training objectives are used to generate agents corresponding to different hospital departments, different medical service processes, and different user services. Specific agents can continuously learn from specific data (such as data from specific hospital departments, specific medical service processes, specific user services, etc.) to achieve self-optimization and evolution, thereby better handling the corresponding tasks.

[0198] In some embodiments of this specification, the configuration of various intelligent agents in the hospital can be customized to enhance the adaptability and application scope of the intelligent agents, thereby significantly improving the accuracy and efficiency of the user services supported by the intelligent agents, while also enhancing the patient's treatment experience.

[0199] In some embodiments, the hospital management system 400 may further include a processing device. The processing device can process data and / or information acquired from the hospital management system 400. In some embodiments, the processing device can receive information and / or instructions input by the user 410 through the interface 420, and provide corresponding feedback after processing the information and instructions. For example, the processing device can receive update information related to a digital twin corresponding to a hardware device from a manager's terminal presenting the interface 420, and control the hardware device to update its configuration based on the update information. As another example, the processing device can receive update information related to agent input through the interface 420, and utilize the agent to perform specific operations based on the update information to provide user services.

[0200] Figure 6 This is a schematic diagram of an exemplary digital twin 431 according to some embodiments of this specification.

[0201] like Figure 6As shown, a digital twin includes one or more first digital twins 4311. For each first digital twin 4311, mapping the state of the associated physical entity may include updating the first digital twin 4311 based on updates to the state of the associated physical entity. For example, one or more first digital twins 4311 may include a digital twin corresponding to a public area of ​​a hospital. When the state of the public area is updated, the first digital twin corresponding to the public area is also updated.

[0202] In some embodiments, the update of the state of the associated physical entity is based on the detection of real-time information about the associated physical entity. For example, an agent or machine learning model can be used to process the real-time information of the associated physical entity to determine whether the state of the associated physical entity has been updated. Optionally, the agent or machine learning model can further process historical data of the associated physical entity to detect state updates.

[0203] In some embodiments, real-time information about the associated physical entity may include information collected by hospital-related hardware devices, including one or more of sensing devices, user terminals, and medical service equipment. Sensing devices may include image sensors, sound sensors, temperature sensors, humidity sensors, particle sensors, or similar devices, or any combination thereof. User terminals may include patient terminals, doctor terminals, administrator terminals, or public terminals within the hospital. Medical service equipment may include medical imaging equipment, examination equipment, etc. Further descriptions of the hardware devices can be found elsewhere in this specification, for example, Figure 1 And related descriptions. In some embodiments, real-time information may be collected by the associated physical entity itself.

[0204] For example, for a digital twin of a hospital's check-in area, the real-time information of the check-in area can include patient flow data collected by image sensors in the check-in area and patient check-in information collected by check-in terminal devices. Updates to the check-in area's status can be obtained based on the detection of patient flow data and patient check-in information.

[0205] In some embodiments, one or more first digital twins may include digital twins corresponding to public areas of the hospital. Monitoring of public areas can be implemented based on the digital twins corresponding to the public areas of the hospital. For example, public areas may include check-in areas, waiting rooms, treatment areas, treatment rooms, operating areas, operating rooms, and similar areas, or any combination thereof. In some embodiments, the digital twins corresponding to public areas may reflect a digital twin view of the public areas, which may be generated based on real-time information about the public areas. The digital twin view can be used to monitor, analyze, and predict the behavior and operation of the public areas in real time to obtain the current state of the public areas. In some embodiments, the digital twin view of the public areas may present a real-time 3D map of the public areas and monitoring indicators of the public areas. Monitoring indicators may include user-related monitoring indicators, event-related monitoring indicators, device-related monitoring indicators, and any combination thereof.

[0206] For example, Figure 7A This is a schematic diagram of a digital twin view of a check-in area according to some embodiments of this specification. For example... Figure 7A As shown, the digital twin view of the check-in area can display a real-time 3D map of the check-in area, monitoring indicators related to patient flow in the check-in area, and monitoring indicators related to the check-in devices in the check-in area. Twin View

[0207] As another example, Figure 7B This is a schematic diagram illustrating a digital twin view of a waiting room according to some embodiments of this specification. Figure 7B As shown, the digital twin view of the waiting room can display a real-time 3D map of the waiting room, a monitoring view related to the waiting status of patients in the waiting room, a monitoring view related to events in the waiting room, and a monitoring view related to the environmental status of the waiting room.

[0208] As another example, Figure 7C This is a schematic diagram illustrating a digital twin view of an inquiry area according to some embodiments of this specification. Figure 7C As shown, the digital twin view of the inquiry area can display a real-time 3D map of the inquiry area, a monitoring view related to the medical staff scheduling of the inquiry area, a monitoring view related to the status of the consultation rooms (such as usage or idle status), a monitoring view related to the hardware and software resources of the inquiry area, and consultation room windows, etc. When a consultation room window is clicked, the corresponding digital twin view of the consultation room will be displayed.

[0209] As another example, Figure 7D This is a schematic diagram of a digital twin view of a consultation room according to some embodiments of this specification. The consultation room can correspond to, for example... Figure 7C The query area is shown. For example... Figure 7D As shown, the digital twin view of the clinic can present a real-time 3D map of the clinic, monitoring views related to clinic events, monitoring views related to clinic treatment, and monitoring views related to clinic hardware and software resources.

[0210] As another example, Figure 7E This is a schematic diagram of a digital twin view of the surgical area according to some embodiments of this specification. For example... Figure 7E As shown, the digital twin view of the surgical area can display a real-time 3D map of the surgical area, monitoring views related to personnel, monitoring views related to the surgical schedule, monitoring views related to events, monitoring views related to the operating room status (such as usage or idle status), monitoring views related to the hardware and software resources of the surgical area, and operating room windows, etc. The digital twin view of the operating room is displayed when the operating room window is clicked.

[0211] As another example, Figure 7F This is according to some embodiments shown in this specification. Figure 7E A schematic diagram of a digital twin view of the operating room within the surgical area. (See diagram below.) Figure 7F As shown, the digital twin view of the operating room can present a real-time 3D map of the operating room, a monitoring view related to the surgery in the operating room, a monitoring view related to the hardware and software resources of the operating room, a monitoring view related to the medical images acquired in the operating room, and a monitoring view related to events in the operating room (such as online consultations).

[0212] In some embodiments of this specification, the real-time status of the public area can be monitored through a first digital twin corresponding to the public area, so that department managers can accurately control and optimize the allocation of medical resources.

[0213] In some embodiments, one or more first digital twins may include digital twins corresponding to medical services. The digital twins corresponding to medical services can be used to evaluate these services. For example, the digital twins corresponding to medical services may reflect operational metrics of the medical services, which are used to evaluate the quality, efficiency, and profitability of the medical services. In some embodiments, medical services may include registration services, treatment and nursing services, routine surgical procedures, medical consultation services, inpatient services, departmental surgical services, or similar services, or any combination thereof.

[0214] For example, Figure 8A This is a schematic diagram of a digital twin corresponding to an outpatient registration service, as illustrated in some embodiments of this specification. For example... Figure 8AAs shown, the digital twin corresponding to the registration service can reflect the service's operational metrics. Exemplary operational metrics for the registration service may include online registration rate (e.g., 50%), appointment time slot heatmap, registration time distribution, or any combination thereof.

[0215] As another example, Figure 8B This is a schematic diagram of digital twins corresponding to treatment and care services illustrated in some embodiments of this specification. For example... Figure 8B As shown, the digital twins corresponding to treatment and care services can reflect the operational metrics of those services. Exemplary operational metrics for treatment and care services may include operational compliance rates (e.g., 80%), documentation compliance rates (e.g., 64%), documentation rating rankings, documentation rating details, and any combination thereof.

[0216] As another example, Figure 8C This is a schematic diagram of a digital twin corresponding to routine surgical procedures as illustrated in some embodiments of this specification. For example... Figure 8C As shown, the digital twin corresponding to routine surgical operation services can reflect the operational metrics of routine surgical operation services. Exemplary operational metrics for routine surgical operation services may include surgical level distribution, surgical delay rate (e.g., 14%), surgical safety score achievement rate (e.g., 87%), personnel with unsatisfactory safety scores, or any combination thereof.

[0217] As another example, Figure 8D This is a schematic diagram of a digital twin corresponding to a medical consultation service, as illustrated in some embodiments of this specification. For example... Figure 8D As shown, the digital twin corresponding to the medical consultation service can reflect the operational indicators of the medical consultation service. Exemplary operational indicators for the medical consultation service may include medical quality, operational efficiency, service quality, etc., or any combination thereof. Medical quality may include high-risk data (e.g., diagnosis rate (e.g., 27%), treatment rate (e.g., 50%)), key data trends, prescription data trends, etc., or any combination thereof. Operational efficiency may include costs and revenue, overall equipment efficiency, business volume, physician workload, etc., or any combination thereof. Service quality may include patient service data, patient satisfaction, increase in treatment costs (e.g., 15%), increase in drug costs (e.g., 4%), etc., or any combination thereof.

[0218] As another example, Figure 8E This is a schematic diagram of a digital twin corresponding to inpatient services according to some embodiments of this specification. For example... Figure 8EAs shown, the digital twin of inpatient services can reflect the operational indicators of inpatient services. Exemplary operational indicators of inpatient services may include service capacity, safety and quality, operational efficiency, medication quality, etc., or any combination thereof. Operational efficiency may include Diagnosis Related Group (DRG) cost index, DRG time index, revenue and expenditure, etc., or any combination thereof. Medication quality may include antibiotic use intensity, drug use review and supervision, nursing quality (e.g., high-quality care, average length of care, etc.), etc., or any combination thereof.

[0219] As another example, Figure 8F This is a schematic diagram of a digital twin corresponding to a departmental surgical service, as illustrated in some embodiments of this specification. For example... Figure 8F As shown, the digital twin corresponding to the surgical services in a department can reflect the operational indicators of those services. Exemplary operational indicators for surgical services may include service capacity, anesthesia quality, surgical safety and quality, operational efficiency, or any combination thereof. Service capacity may include day surgery rate (e.g., 12%), Level 4 surgery rate (e.g., 13%), etc. Anesthesia quality may include unplanned reoperation rate, PACU transfer delay rate, etc. Surgical safety and quality may include mortality rate, unplanned reoperation rate, complication rate, etc. Operational efficiency may include surgical cancellation rate (e.g., 17%), operating room utilization rate (e.g., 85%), revenue and expenditure, infection control, etc.

[0220] It should be noted that, Figures 8A to 8F The operational metrics for healthcare services shown are for illustrative purposes only and may be replaced by any other operational metrics. For example, operational metrics for registration services may include the ratio of online to offline registration, and the registration time for online and offline registration. In some embodiments, the operational metrics for healthcare services may be configured by the relevant administrator. In some embodiments, the administrator may also interact with interface 420 to obtain other operational metrics.

[0221] In some embodiments of this specification, by managing the first digital twin, managers can identify key issues in the healthcare service process, so as to intervene in the operation of healthcare services in a timely manner and adjust strategies, thereby improving the management quality of healthcare services.

[0222] In some embodiments, one or more first digital twins may include other digital twins that are updated based on updates to the state of the associated physical entity. For example, a first digital twin may include a digital twin of a patient or a patient's organ, which can be updated based on new medical data of the patient acquired (e.g., new medical images, new examination data). As another example, a first digital twin may include a digital twin of a hardware device, which can be updated based on updates to the hardware device's usage status, operating parameters, etc.

[0223] In some embodiments, for each of at least a portion of one or more first digital twins, in response to detecting that an update to the state of the associated physical entity is normal, the first digital twin is updated using a first method; in response to detecting that an update to the state of the associated physical entity is abnormal, the first digital twin is updated using a second method. The state update of the associated physical entity generally conforms to preset rules, such as an update time less than a certain threshold. For example, for an operating room in use, if the state of the operating room has not been updated for a period of time, it indicates that the state update of the operating room is abnormal. As another example, if the updated state of the associated physical entity is abnormal, then the state update of the associated physical entity is considered abnormal.

[0224] The first approach can differ from the second approach. That is, the update method of the first digital twin can differ depending on whether the associated physical entity experiences abnormal or normal state changes. For example, when a normal state update of the associated physical entity is detected, the first digital twin may display a first marker symbol (or a first color); when an abnormal state update of the associated physical entity is detected, the first digital twin may display a second marker symbol (or a second color) different from the first marker symbol (or first color). As another example, when a normal state update of the associated physical entity is detected, the first digital twin may not display any marker symbol; when an abnormal state update of the associated physical entity is detected, the first digital twin may display a specific marker symbol. In this way, the first digital twin can be used for anomaly monitoring of associated physical entities, facilitating timely adjustments to the associated physical entities.

[0225] In some embodiments, digital twin 431 includes one or more second digital twins 4312 that can be updated via an interface. For each second digital twin 4312, the state of the mapped associated physical entity includes updates to the associated physical entity based on updates to the second digital twin 4312. In some embodiments, the second digital twin 4312 can be used to update the configuration of the associated physical entity. Specifically, after updating the second digital twin, the configuration of the associated physical entity can be updated based on the updated second digital twin.

[0226] In some embodiments, one or more second digital twins may include a digital twin corresponding to a hardware device, which may reflect the parameters of the hardware device. It can be used to update / set the parameters of the hardware device. For example, the hardware device may include a common terminal device (e.g., a display device or XR device), a smart hospital bed, a smart nursing cart, a smart surgical terminal, a smart robotic nurse, etc.

[0227] In some embodiments, the hardware device may include a display device for displaying information related to medical services. A digital twin of the hardware device may reflect the display parameters of the display device, which can be set or updated by the user 410 through interface 420. For example, the user 410 can adjust the content displayed by updating the digital twin of the hardware device.

[0228] For example, Figure 9A This is a schematic diagram illustrating a display device in a waiting room according to some embodiments of this specification. For example... Figure 9A As shown, the display device can present consultation room information (e.g., Cardiology F4A Consultation Room 01), pre-consultation QR code, doctor-related information, information about currently seeing patients, and information about waiting patients. As another example, Figure 9B This is a schematic diagram of a display device in a consultation room according to some embodiments of this specification. For example... Figure 9B As shown, the display device can display pre-consultation information, consultation suggestions, electronic medical records, remote medical escort services, etc. As another example, Figure 9C This is a schematic diagram of a display device in a hospital ward according to some embodiments of this specification. For example... Figure 9C As shown, the display device can present daily schedules, agent services, and homepages (e.g., care plans, hospital consultations, doctor rounds, visitation requests, etc.). As another example, Figure 9D This is a schematic diagram of a display device in a surgical waiting area according to some embodiments of this specification. For example... Figure 9D As shown, the display device can present surgical notifications (such as surgical sequence number, surgical start time, operating room number, patient name, surgeon's name, surgical status, etc.), monitoring information of the waiting area, and artificial intelligence information consultation window.

[0229] In some embodiments, the hospital management 400 may further include a processing device. The processing device can receive update information related to a digital twin corresponding to a hardware device from a manager's terminal presenting an interface, and control the hardware device to update its configuration based on the update information. Further description regarding controlling the hardware device to update its configuration based on update information can be found in other parts of this specification (e.g., Figure 10 (and related descriptions).

[0230] In some embodiments, one or more second digital twins may include a digital twin corresponding to a user service, which may reflect parameters of the user service. In some embodiments, the user service may be obtained through a patient space application installed on a patient's terminal or a medical space application installed on a doctor's terminal.

[0231] In some embodiments, the digital twin corresponding to the user service can be used to update / set parameters of the user service. For example, the parameters of the user service may include the way the user service is used, the requirements that the user needs to meet when using the user service, the content of the user service, and any combination thereof. Specifically, after the digital twin corresponding to the user service is updated, it reflects the updated parameters of the user service. The updated parameters of the user service can be sent to a processing device. Further, the processing device can update the parameters of the user service based on the updated parameters.

[0232] In some embodiments, one or more second digital twins may include a digital twin corresponding to a medical service process, the digital twin of which reflects the parameters of the medical service process.

[0233] In some embodiments, parameters of a medical service process may include standard operating procedures (SOPs), which define the standard steps in the medical service process. For example, the SOP for a medical consultation service process may include registration, waiting, and consultation. In some embodiments, the SOP may further specify the data acquisition protocol for each standard step. The data acquisition protocol for each standard step may specify the type of data collected and the method of data collection in that standard step.

[0234] In some embodiments, standard operating procedures can break down healthcare service processes into detailed standard steps, and corresponding data acquisition protocols can identify potential data sources associated with each standard step as much as possible. Therefore, this approach enables the collection of more comprehensive, granular, and real-time data related to healthcare service processes, facilitating subsequent evaluation of various aspects of the healthcare service process and thereby optimizing and improving the overall efficiency of the hospital management system.

[0235] In some embodiments, the second digital twin corresponding to a medical service process can be configured to update / set parameters of the medical service process. In some embodiments, updating the medical service process parameters can be implemented in a manner similar to updating parameters of a user service.

[0236] Digital twins can be created using data acquired from sensors and other sources to dynamically simulate real-world physical entities in real time. According to some embodiments of the hospital management system provided in this specification, the deployed digital twin can be used for monitoring, analysis, simulation, and control, thereby providing valuable information to optimize and improve the overall efficiency of the hospital management system.

[0237] Figure 10This is an exemplary schematic diagram illustrating a method for updating hardware device configuration according to some embodiments of this specification. In some embodiments, process 1000 may be stored in memory as program instructions and invoked and / or executed by a processing device (e.g., processing device 210).

[0238] Step 1010: Receive update information of the digital twin corresponding to the hardware device from the administrator terminal of the presentation interface.

[0239] The administrator terminal can install a management space application. For example, after a user logs into the management space application, an interface for managing hospital resources is presented (e.g., interface 420). The user can input a first request via text, voice, touch interface, or specific gestures to view the digital twin corresponding to the hardware device. For example, the user can input the first request by conversing with a virtual character presented on the interface. The first request is sent to a processing device, which can retrieve the corresponding digital twin from a storage device or generate a corresponding digital twin based on real-time information from the hardware device. The processing device enables the administrator terminal to present the digital twin through the interface. Then, the user can input a second request through the interface to update the digital twin, and the updated information of the digital twin can be transmitted from the administrator terminal to the processing device.

[0240] For example only, such as Figure 6 As described above, the digital twin corresponding to a hardware device can reflect the parameters of the hardware device. After the digital twin corresponding to the hardware device is updated, it can reflect the updated parameters of the hardware device. The update information of the digital twin corresponding to the hardware device may include the updated parameters of the hardware device, which can be sent to the processing device.

[0241] Step 1020: Control the hardware device to update its configuration based on the update information.

[0242] In some embodiments, the processing device may store update information in a storage device and send an update notification to a hardware device, enabling the hardware device to retrieve the update information from the storage device and update its configuration. Specifically, after receiving the update notification, the hardware device can retrieve the update parameters from the storage device and update the values ​​of the corresponding parameters according to the update parameters. In some embodiments, the processing device may utilize a subscription mechanism to automatically send the update notification to the hardware device corresponding to the update information after receiving the update information.

[0243] In some embodiments, updates to hardware device configuration may affect user services. For example, if a registration terminal updates its configuration (e.g., requiring the input of a patient's temperature), the registration services provided to the patient will change. Specifically, the processing device may include software modules for providing user services. The hardware device configuration may be associated with the software modules, which may subscribe to update notifications of the hardware device's configuration parameters. When the hardware device's configuration parameters are updated, the processing device may receive the updated hardware device configuration and store it in a storage device. Further, the processing device may send update notifications to the software modules, enabling the software modules to retrieve the updated configuration from the storage device to update the user services.

[0244] In some embodiments, the hardware device can provide multiple user services. The configuration parameters of the hardware device can correspond to different software modules. In some embodiments, the correspondence between the software modules and the configuration parameters of the hardware device can be determined by an intelligent agent (e.g., agent 432). This correspondence can indicate that when a specific configuration parameter of the hardware device is updated, the corresponding software module needs to update its user services. As the hospital develops, the intelligent agent can learn this correspondence more accurately based on increasing historical data, thereby continuously updating the subscription mechanism and making management more intelligent.

[0245] Figure 12 This is a schematic diagram illustrating an exemplary process of providing user services to relevant users of a medical service process using a first intelligent agent, according to some embodiments of this specification. The first intelligent agent corresponds to the medical service process. In some embodiments, process 1200 may be stored in memory as instructions and invoked and / or executed by the first intelligent agent (e.g., a first intelligent agent implemented by processing device 210).

[0246] Step 1210: The first intelligent agent can monitor the updates of data related to the patient's medical service process.

[0247] like Figure 4 The first intelligent agent may include a consultation intelligent agent, an inpatient intelligent agent, a surgical intelligent agent, etc. The medical service process may include a medical consultation service process, an inpatient service process, a surgical service process, etc., or any combination thereof.

[0248] In some embodiments, a medical service process may include multiple stages. In some embodiments, each stage may correspond to one or more medical services. For example, multiple stages of an inpatient service process may include an admission procedure, an admission inquiry stage, an inpatient procedure, a discharge procedure, a follow-up procedure, or any combination thereof. Each stage may correspond to one or more inpatient services. For example, the admission procedure may correspond to admission procedures, the admission inquiry stage may correspond to admission inquiries, the inpatient procedure may correspond to ward services (e.g., nursing services, ward rounds, visitation services, etc.), the discharge procedure may correspond to discharge services, and the follow-up procedure may correspond to follow-up services.

[0249] Data related to the healthcare service process can characterize the progress of the healthcare service process, the patient's status during the healthcare service process, and / or multiple aspects of the healthcare service process. For example, data related to the healthcare service process may include data related to each stage of the healthcare service process. For example, data related to the healthcare service process may include data related to the healthcare services provided to the user during the healthcare service process.

[0250] In some embodiments, the first intelligent agent can monitor updates to the relevant data of the medical service process (also known as data updates) by monitoring one or more data sources that collect relevant data of the medical service process.

[0251] Data source refers to the source (such as hardware devices) that provides (e.g., collects) data related to the medical service process.

[0252] For example, the data source may include sensing devices that collect perceived information. Exemplary sensing devices may include image sensors, acoustic sensors, temperature sensors, humidity sensors, barometric pressure sensors, and any combination thereof.

[0253] For example, the data source may include terminal devices that interact with users involved in the healthcare service process. For instance, terminal devices may include those interacting with the patient's doctor, those interacting with the patient, public terminal setups in the hospital, those interacting with nurses, terminal devices for remote visitors, and any combination thereof. Taking an inpatient service process as an example, terminal devices may include those located in the patient's room, configured to display data to the patient (e.g., notifications, virtual avatars, image data of remote visitors) and / or receive instructions or requests input by the patient. Patients may interact with the terminal devices via input devices (e.g., controllers), voice, gestures, etc. Exemplarily, terminal devices may include presentation devices, XR devices, mobile devices, laptops, and any combination thereof.

[0254] For example, the data source may include examination equipment, such as a monitor that collects vital signs data of a patient. Exemplary vital signs data may include heart rate, respiratory rate, body temperature, blood pressure, or any combination thereof.

[0255] For example, the data source may include a medical examination department that collects patient examination results. The medical examination department may include a medical imaging department, a clinical laboratory, or any combination thereof. The medical imaging department is equipped with medical imaging equipment such as computed tomography (CT) equipment, digital subtraction angiography (DSA) equipment, magnetic resonance (MR) equipment, ultrasound equipment, positron emission tomography (PET) equipment, single-photon emission computed tomography (SPECT) equipment, positron emission tomography-computed tomography (PET-CT) equipment, positron emission tomography-magnetic resonance imaging (PET-MRI) equipment, or any combination thereof. The clinical laboratory is configured to perform clinical examinations on the examinee. For example, clinical examinations may include complete blood counts, urinalysis, biochemical tests, immunoassays, instrumental examinations, or any combination thereof.

[0256] For example, the data source may include nursing devices for providing nursing services to patients and / or assisting healthcare providers (e.g., doctors, nurses, etc.) in providing nursing services. Exemplary nursing devices may include patient care robots, intelligent nursing carts, etc. Patient care robots may include sensors, robotic arms, actuators, user interfaces, or similar devices, or any combination thereof. Patient care robots can provide nursing services to patients, such as assisting them with drinking water, eating, or taking medication. Intelligent nursing carts may have autonomous driving capabilities, enabling them to move to different locations within the hospital. For example, an intelligent nursing cart may be configured to guide nurses to patient rooms to perform examinations or nursing procedures. As another example, an intelligent nursing cart may be configured to present guidance information to guide nurses in performing examinations or nursing procedures. Optionally, an intelligent nursing cart may include one or more examination devices and / or nursing tools for nurses to use in performing examinations and / or nursing procedures.

[0257] It should be noted that the above description of data sources is for illustrative purposes only and is not intended to limit them. The first agent can monitor any data source that can collect data related to the healthcare service process.

[0258] Because data sources are diverse, data related to healthcare service processes also includes various types of data, such as sensory information, examination data, interaction data, clinical data, and medical order data. In some embodiments, data related to healthcare service processes can be multimodal data, which may include multiple types of data and multidimensional data.

[0259] In some embodiments, the data source may also include Internet of Things (IoT) devices that collect IoT data. IoT devices are devices that integrate sensing capabilities, processing capabilities, software algorithms, and other technologies, and are capable of connecting and exchanging data with other devices or systems via the Internet or other communication networks. For example, sensing devices, smart nursing carts, patient care robots, and medical imaging equipment can communicate via wireless networks; these devices can be referred to as IoT devices.

[0260] In some embodiments, the data source can be a standalone device or integrated into another device. For example, a sound sensor can be part of a hospital bed or terminal device.

[0261] In some embodiments, a data update can be detected when one or more of a plurality of data sources acquire updated data that the first agent has not yet processed. For example, a vital signs monitor may acquire a patient's heart rate data hourly, and when new heart rate data is acquired, the first agent may detect a data update in the vital signs monitor.

[0262] In some embodiments, the first intelligent agent can directly establish a communication connection with the data source and directly monitor it. For example, when the data source transmits updated data to the first intelligent agent, the first intelligent agent can detect the data update from the data source. As another example, the first intelligent agent can establish a communication connection with a storage device (such as storage device 230) that stores relevant data of the medical service process collected by the data source, and monitor the data source by monitoring the storage device. For instance, when the storage device receives updated data from the data source, the first intelligent agent can detect the data update from the data source.

[0263] In some embodiments, the first intelligent agent can monitor different data sources as the patient is at different stages of the healthcare process. For example, the first intelligent agent can determine the patient's current stage in the healthcare process and monitor the data source corresponding to that stage, or a portion thereof. For instance, in an inpatient process, when the patient is in the admission check-in stage, the first intelligent agent can monitor sensing devices within the ward.

[0264] In some embodiments, the first intelligent agent can monitor the data source according to a preset data acquisition protocol corresponding to the medical service process. The preset data acquisition protocol may include a data acquisition protocol corresponding to a stage of the medical service process. The data acquisition protocol specifies the data source (such as hardware device) corresponding to the data to be collected in each stage of the medical service process, the data interface standard corresponding to the data source, and the data quality standard corresponding to the data source.

[0265] In some embodiments of this specification, by providing personalized monitoring for patients, continuous status detection can be achieved, thereby enabling timely responses to patients' needs and improving the efficiency and quality of user services.

[0266] In some embodiments, when a data update to the data source is detected, the first agent may continue to execute step 1220. Simultaneously, the first agent may continue to execute step 1210 to continuously monitor the data source.

[0267] Step 1220: In response to the detection of relevant data, including updated data, on the medical service process, the first agent performs detection of events of interest based on the updated data.

[0268] Updated data refers to data collected by a data source that has not yet been processed by the first intelligent agent. For example, when the data source is an IoT device, the updated data includes IoT data. Another example is when the data source is a sensing device, the updated data includes sensory information collected by the sensing device, such as image data collected by an image sensor or acoustic data collected by an acoustic sensor. Yet another example is when the data source is a doctor's terminal device related to the patient, the updated data includes patient-related input data entered by the doctor through the terminal device. Yet another example is when the data source is a vital signs monitor, the updated data includes the patient's vital signs. Finally, when the data source is a medical examination department, the updated data includes the patient's examination results. It should be noted that updated data can be obtained directly from the data source or from storage devices.

[0269] An Event of Interest (EOI) is an event or action that requires attention. In some embodiments, EOI detection refers to detecting and processing updated data collected from a data source to determine whether one or more EOIs have occurred. For example, EOIs may include a patient arriving at a designated location (e.g., a ward, examination room, or examination room), an action performed on a patient by a doctor (e.g., instructions given to a patient during ward rounds), an admission examination performed on a patient, a nursing procedure or medical examination performed on a patient, a service request made by a patient, the retrieval or updating of a patient's medical orders, an abnormality in a patient's physiological state, or any combination thereof.

[0270] In some embodiments, the data source may include multiple data sources for collecting relevant data on the same event of interest. For example, image sensors and sound sensors in the same room (e.g., a hospital ward) are used to collect relevant data on the same event of interest occurring in that room. For instance, in an inpatient service process, image sensors and sound sensors in a hospital ward may collect relevant data on the same event of interest occurring in that ward (e.g., a patient being admitted to the ward, or at least one doctor making rounds in the ward).

[0271] In some embodiments, the data source may include a data source for acquiring relevant data on multiple events of interest. For example, it may be an image sensor in the same room (e.g., a hospital ward) for acquiring relevant data on multiple events of interest occurring in the same room, wherein the multiple events of interest include admission examinations of patients, nursing procedures performed on patients, or medical examinations.

[0272] In some embodiments, the first agent may perform interest event detection according to interest event detection rules. Interest event detection rules refer to the rules that must be followed when performing interest event detection. For example, interest event detection rules may include specified interest events to be detected, algorithms or techniques for detecting specific interest events, algorithms or techniques for analyzing data collected from specific data sources, interest events corresponding to different stages in a medical service process, interest events corresponding to different types of patients, etc., or any combination thereof.

[0273] In some embodiments, the event of interest (ROI) detection rules may be determined based on historical ROI detection records and / or manually set by a user (e.g., a doctor, nurse, technician, etc.). For example, a first agent may perform ROI detection on updated data based on the type of updated data. For instance, when the updated data is image data acquired by an image sensor, ROI detection may include performing at least one of moving object detection, anomaly detection, behavior detection, or identity recognition on the image data. As another example, when the updated data is a speech signal acquired by an acoustic sensor, ROI detection may include performing at least one of speech content recognition, speaker recognition, or key content extraction on the speech signal. As yet another example, when the updated data is a value of a physiological parameter, ROI detection may include determining whether the data difference between the physiological parameter value and a historical value exceeds a data difference threshold, determining whether the physiological parameter value exceeds a data range, etc. The data difference threshold and / or data range may be specified in the ROI detection rules. For example, assuming a patient's heart rate ranges from 50 to 120 beats per minute, when the vital signs monitor collects a heart rate of 130 beats per minute, the first agent can determine that the patient's heart rate is outside the range and that an event of interest has occurred (i.e., the patient's physiological state is abnormal).

[0274] In some embodiments, each stage of a medical service process may correspond to one or more events of interest, and different stages of the medical service process may correspond to different types of events of interest. A first intelligent agent can perform events of interest detection on updated data based on the current stage of the medical service process. For example, the first intelligent agent can determine the current stage of an inpatient service process and, based on the current stage, determine the types of events of interest that need to be detected. Furthermore, the first intelligent agent can perform events of interest detection on updated data according to the types of events of interest.

[0275] Taking the inpatient service process as an example, when a patient is in the admission process, the events of interest that the first intelligent agent determines to be detectable may include the patient being admitted to a ward, the patient meeting the conditions for admission examination, and the admission examination performed on the patient. As another example, when a patient is in the hospitalization process, the events of interest that the first intelligent agent determines to be detectable may include at least one doctor making rounds in the ward, nursing procedures or medical examinations performed on the patient, the patient initiating a service request, the acquisition or updating of the patient's medical orders, abnormalities in the patient's physiological state, and instructions issued by the doctor to the patient.

[0276] In some embodiments of this specification, the detection of events of interest is performed based on the current stage of the medical service process. Only specific types of events of interest need to be detected or tracked, which can reduce the amount of data that needs to be processed, thereby reducing the processing load of the first intelligent agent and improving the efficiency of event of interest detection.

[0277] like Figure 4 The basic configuration data of the intelligent agent includes key information that the agent relies on when providing specific services. In some embodiments, interest event detection can be performed based on updated basic configuration data. For example, the first intelligent agent can use an updated knowledge database corresponding to a medical service process as a reference to determine interest event detection rules for the medical service process, and perform interest event detection according to the determined interest event detection rules. In some embodiments, the first intelligent agent can learn interest event detection rules based on both updated basic configuration data and historical records of interest event detection.

[0278] In some embodiments, in response to detecting an event of interest, the first agent may continue to execute step 1230. During this period, the first agent may also continue to execute steps 1210 and 1220 to continuously monitor the data source and detect events of interest.

[0279] Step 1230: In response to the detection of an event of interest, the first agent performs one or more preset operations corresponding to the event of interest to provide user services to relevant users in the medical service process.

[0280] In some embodiments, one or more predetermined operations may be performed based on updated data and / or updated basic configuration data corresponding to the first intelligent agent. Updated basic configuration data includes the latest version of the basic configuration data of the first intelligent agent, which has been updated or confirmed by the user. For example, user 410 may update a portion of the basic configuration data of the first intelligent agent through interface 420. The updated portion of the basic configuration data and the original basic configuration data may be stored as updated basic configuration data of the first intelligent agent in a storage device for later use.

[0281] The preset operation corresponding to the event of interest refers to the operation that needs to be performed when the event of interest occurs. In some embodiments, the preset operation may include general operations and / or specific operations. A general operation is an operation that needs to be performed whenever the event of interest occurs, regardless of the type of event of interest. For example, a general operation may include generating a record related to the event of interest. That is, as soon as an event of interest is detected, the first agent generates a record of the event of interest based on updated data related to the event of interest and / or updated basic configuration data (e.g., updating the record template, knowledge database, and dictionary in the basic configuration data). As an example, the record of the event of interest may include registration records, admission records, nursing records, ward round records, visitation records, discharge records, follow-up records, consultation records, surgical records, etc., or any combination thereof. As another example, a general operation may include transmitting the record of the event of interest to the corresponding user for confirmation, or transmitting it to a storage device for storage. In some embodiments, updating the knowledge database and dictionary in the basic configuration data may be used to convert natural language into medical or professional terms, and updating the record template in the basic configuration data may be used to organize medical or professional terms into structured records.

[0282] A specific action refers to an action performed when a specific type of event of interest occurs. For example, updating a patient's daily schedule based on updated data can be considered a specific action corresponding to the event of interest of updating patient medical orders. Similarly, sending a notification related to an event of interest to a healthcare provider can be considered a specific action corresponding to the event of interest of an abnormal physiological state in a patient.

[0283] For illustrative purposes, the inpatient service process will be explained below.

[0284] For example, when the event of interest includes a patient's admission to a ward, one or more preset operations may include: determining the content of the inquiry to be conducted on the patient after admission to the ward (also known as the first inquiry content of the first inquiry) based on the patient's patient data and the inquiry template in the updated basic configuration data; causing the terminal device in the ward to conduct an inquiry based on the inquiry content; obtaining the sensing information collected by one or more sensing devices in the ward during the inquiry (also known as the first sensing information); and generating the patient's admission record based on the sensing information and the admission record template in the updated basic configuration data.

[0285] As another example, when the event of interest includes the retrieval or updating of patient medical orders, one or more pre-defined operations may include determining the patient's daily schedule for each day of hospitalization based on the patient's patient data and medical orders or updated medical orders, and displaying the daily schedule to the patient via a terminal device in the patient's ward, or to the nurse corresponding to the patient via a nurse's terminal device. The daily schedule may include at least one medical procedure that needs to be performed on the patient each day.

[0286] For example, when the event of interest includes at least one doctor making rounds in a patient's ward, one or more preset operations may include acquiring sensing information (also known as fourth sensing information) collected by one or more sensing devices in the ward when at least one doctor makes rounds in the ward, and generating a ward round record based on the sensing information, updating the ward round record template in the basic configuration data, updating the knowledge database in the basic configuration data, etc.

[0287] As another example, when the event of interest includes the patient's discharge, one or more pre-defined actions may include determining the patient's follow-up plan based on the patient's target hospitalization record and a knowledge database updated in basic configuration data. The follow-up plan may include one or more follow-ups to be performed at one or more scheduled times. For each follow-up, one or more pre-defined actions may further include alerting the attending physician's terminal device (also referred to as the second terminal device) and the patient's terminal device (also referred to as the third terminal device) respectively, based on the scheduled time of the follow-up.

[0288] In some embodiments, a first agent may determine a correspondence between events of interest and preset operations, and determine one or more preset operations corresponding to the detected events of interest based on the correspondence. The correspondence may indicate that one or more preset operations need to be performed when a specific type of event of interest occurs. For example, the correspondence may be in the form of a lookup table.

[0289] In some embodiments, the correspondence can be predetermined and stored in a storage device, and the first agent can retrieve the correspondence from the storage device. In some embodiments, the first agent can determine the correspondence between events of interest and preset operations based on historical records. In some embodiments, the first agent can determine the correspondence based on updated basic configuration data (e.g., updating the knowledge database in the basic configuration data). In some embodiments, the first agent can learn the correspondence based on both updated basic configuration data and historical records of detected events of interest.

[0290] In some embodiments, one or more preset actions corresponding to an event of interest can be further determined based on the patient's patient data. Patient data may include basic data, health data, historical data, registration data, etc. For example, different types of patients (such as different diseases or different ages) may correspond to different preset actions. As an example only, if the patient has a history of hospitalization at the hospital, the one or more preset actions corresponding to the event of interest, such as the obtained hospitalization guidance request, can be simplified. By determining one or more preset actions corresponding to an event of interest based on patient data, one or more preset actions can be customized for the patient, thereby improving the accuracy of providing hospitalization services and enhancing user satisfaction.

[0291] In some embodiments, one or more preset operations may be performed based on a data source corresponding to an event of interest. For example, when there are multiple data sources that collect data on the same event of interest, one or more preset operations may be performed based on a combination of the same event of interest data collected from the multiple data sources. As an example, for an image sensor and a sound sensor in the same room used to collect data on the event of interest of a patient entering the room, one or more preset operations may be performed based on a combination of the event of interest data collected by the image sensor and the sound sensor.

[0292] As another example, when the data source is a single data source that collects data on multiple events of interest, the preset operations corresponding to at least two of the multiple events of interest can be different. For example, in a hospital service process, acoustic sensors in the ward can collect acoustic data on multiple different events of interest occurring in the ward, such as a patient's admission to the ward or a doctor's rounds, and one or more preset operations corresponding to these different events of interest can be different.

[0293] In some embodiments, a preset operation corresponding to an event of interest can be executed immediately after the event of interest is detected. For example, when a patient's physiological state is abnormal, the first intelligent agent can cause the terminal device to issue an alarm. In some embodiments, a preset operation corresponding to an event of interest can be executed after the event of interest is completed. For example, an event of interest record can be generated in response to the detection of the completion of an event of interest.

[0294] In some embodiments of this specification, monitoring the data source that captures information about a patient's healthcare service process helps to detect data updates and events of interest in a timely manner, thereby triggering corresponding preset operations. Therefore, user services can be provided to users automatically and efficiently, improving service efficiency and quality. Furthermore, the monitored data source collects multimodal data at different stages of the entire healthcare service process, enabling patient-centered healthcare and comprehensive user services.

[0295] In some embodiments, the first agent can learn rules for detecting events of interest from historical records and perform events of interest detection based on these rules. The rules for detecting events of interest refer to the rules governing how to perform events of interest detection on updated data and / or updated basic configuration data. For example, the first agent can learn from historical records the types of events of interest that need to be monitored, how to effectively detect events of interest, and the data that needs to be analyzed to detect events of interest.

[0296] In some embodiments, the first agent can learn the correspondence between events of interest and preset operations from historical records, and determine one or more preset operations corresponding to the events of interest based on the correspondence. For example, the first agent can learn the operations to be performed when an event of interest occurs from historical records.

[0297] In some embodiments, the first agent can further learn rules for detecting events of interest and / or the correspondence between events of interest and preset operations based on patient data from different patients. For example, the first agent can determine different rules for detecting events of interest and their different preset operations for different types of patients (such as different diseases or different ages). As an example only, for different patients of different ages, the first agent can determine different heart rate ranges for detecting events of interest.

[0298] The first intelligent agent can continuously learn the rules for detecting events of interest and / or the correspondence between events of interest and preset operations by utilizing big data technology, machine learning technology, and other advanced methods. This enables continuous optimization and improvement of the accuracy, efficiency, and quality of hospital services.

[0299] Figure 13 This is a schematic diagram illustrating an exemplary process of providing user services to a user using a second intelligent agent, according to some embodiments of this specification. The second intelligent agent can be used to implement user services related to stages in a medical service process. In some embodiments, process 1300 can be stored in memory as instructions and invoked and / or executed by the second intelligent agent (e.g., a second intelligent agent implemented by processing device 210).

[0300] Step 1310: Obtain data related to the patient's medical service process.

[0301] In some embodiments, a medical service process may include a medical consultation process, an inpatient service process, a surgical service process, etc. More detailed descriptions of medical service processes can be found elsewhere in this specification. For example, please see [link to documentation]. Figure 12 Step 1210 and its description.

[0302] Data related to each stage of the healthcare service process can be used to reflect the progress of each stage, the patient's status during that stage, and / or various aspects of the process. For example, data related to each stage of the healthcare service process can include information about each healthcare service provided to the user at that stage.

[0303] In some embodiments, relevant data from various stages of the medical service process can be collected by a data source and stored in a storage device. A second intelligent agent can then retrieve this patient-related data from the storage device. Further descriptions of the data source can be found in other parts of this specification (e.g., Figure 12 ).

[0304] Step 1320: Process data based on the updated basic configuration data corresponding to the second intelligent agent.

[0305] like Figure 4 The basic configuration data corresponding to the intelligent agent may include key information that the intelligent agent relies on when providing specific services. When the basic configuration data corresponding to the second intelligent agent is updated, the second intelligent agent can use the updated basic configuration data to perform data processing. Updating the basic configuration data can be obtained through an interface (e.g., interface 420). As shown in Table 1, for an intelligent agent performing hospital admission inquiries, its basic configuration data may include inquiry templates for different diseases, a specialist medical knowledge base, and hospital admission record templates. When the user updates the specialist medical knowledge base or the hospital admission record template through the interface, the second intelligent agent can use the updated specialist medical knowledge base or the updated hospital admission record template to perform data processing.

[0306] In some embodiments, the second intelligent agent can evolve itself based on relevant historical data of medical service process links and artificial intelligence technology, and perform data processing based on rules learned from relevant historical data of medical service process links.

[0307] In some embodiments, different intelligent agents can be trained. These agents can correspond to different medical service processes, different stages of the medical service process, different medical services, different departments, different diseases, and different medical service providers (e.g., nurses, doctors, scanning technicians, hospital managers, etc.). The second intelligent agent can be an agent corresponding to a stage in the medical service process.

[0308] Step 1330: Provide user services to relevant users in the medical service process based on the data processing results.

[0309] User services may include services provided to relevant users at various stages of the healthcare service process. For example, relevant users may be patients, and user services provided to patients may include registration services, pre-consultation services, admission inquiry services, route guidance services, discharge services, follow-up services, or any combination thereof. Alternatively, relevant users may be hospital staff (e.g., doctors, nurses, hospital administrators), and user services provided to hospital staff may include generating records, notifications, and suggestions based on data processing results.

[0310] In some embodiments, the data processing results may include information related to user services and information about relevant users (e.g., department, type, etc.). Information related to user services may include service type (e.g., registration service, pre-registration service, admission inquiry service, route guidance service, discharge service, etc.), content, time, and delivery method. Information about relevant users may include the relevant user's department and user type (e.g., patient, hospital staff (e.g., doctor, nurse, hospital manager)). The second intelligent agent may provide user services to relevant users based on the information corresponding to the data processing results.

[0311] In some embodiments, the second intelligent agent may use a virtual avatar to provide user services to relevant users. Specifically, the virtual avatar corresponding to the second intelligent agent may be presented through a user space application (e.g., a patient space application), and user services may be provided to users through interactions between relevant users (e.g., patients, hospital staff (e.g., doctors, nurses, hospital administrators)) and the virtual avatar in the medical service process.

[0312] User space applications can set permissions for relevant users to access user services. For example, a user space application can be an application installed on a patient terminal device, or it can be a management space application installed on a public terminal in the hospital (such as an XR device).

[0313] A virtual character is a computer-generated person or object that can be used to interact with a relevant user in a digital environment. Virtual characters can be configured to interact with relevant users to provide user services. In some embodiments, a virtual character can be a digital role with appearance features, voice features, etc. Exemplary appearance features may include physical features, skin features, facial features, and clothing features. Voice features may include frequency features, volume features, duration features, quality features, tone features, speech rate features, intonation features, etc., or any combination thereof. In some embodiments, the appearance features and / or voice features of a virtual character can be determined based on the patient's patient data. Patient data may include basic data (e.g., name, age, gender, weight, address, occupation, etc.), health data (e.g., disease type, disease symptoms), historical data (e.g., historical clinical data, historical hospitalization data, etc.), registration data (e.g., target registration records, etc.), etc., or any combination thereof. In some embodiments, patient data may also include the patient's electronic medical record.

[0314] In some embodiments of this specification, by using a second intelligent agent, user services can be provided automatically, thereby reducing the need for a large workforce, lowering operating costs, and improving the efficiency of user services. Furthermore, the second intelligent agent can continuously optimize the learned rules, thereby improving the accuracy, efficiency, and quality of user services.

[0315] It should be noted that the above descriptions of processes 1000, 1200, and 1300 are merely illustrative and do not limit the scope of this specification. Those skilled in the art can make various modifications and changes to the processes under the guidance of this specification. However, these modifications and changes remain within the scope of this specification. For example, the operations of processes 1000, 1200, and 1300 are for illustrative purposes; in some embodiments, one or more operations of processes 1000, 1200, and 1300 may be added or omitted. Furthermore, the order of operations of processes 1000, 1200, and 1300 is not intended to be restrictive.

[0316] Figure 14A This is a schematic diagram illustrating an exemplary process for providing a pre-consultation service according to some embodiments of this specification. The pre-consultation service can be used to collect information about a patient by conducting preliminary inquiries before the patient enters the consultation room for a formal consultation. Specifically, while the patient is waiting, the processing device 210 can conduct a pre-consultation with the patient through the patient's patient terminal device or a waiting terminal configured in the waiting area to alleviate the patient's anxiety while waiting, generate a pre-consultation record template, and provide the record template to the doctor for reference, thereby improving the doctor's consultation efficiency. In some embodiments, at least a portion of process 1400A is executed by a pre-consultation agent configured on the processing device 210 corresponding to the pre-consultation service.

[0317] Step 1410: Determine the content of the pre-consultation inquiry based on the doctor's (e.g., the doctor who registered the patient) department.

[0318] Pre-consultation inquiry is used to conduct preliminary inquiries with the patient before the formal consultation. Pre-consultation inquiry may include multiple rounds of questioning. The inquiry content may include the content of each round of questioning. Alternatively, the inquiry content may only include the content of the first round of inquiry. In some embodiments, the processing device 210 may acquire a pre-consultation record template corresponding to the doctor's department and determine the inquiry content based on the pre-consultation record template.

[0319] In some embodiments, the processing device 210 can obtain known information about the patient (e.g., electronic medical records, chief complaints, etc.) and determine any missing information in the pre-consultation record template that has not yet been collected by comparing it with the known information. Furthermore, the processing device 210 can determine the content of the inquiry based on the missing information.

[0320] In some embodiments, the processing device 210 may use an inquiry model to determine the inquiry content based on known information about the doctor's department and the patient. The inquiry model may include a CNN model, an RNN model, an LSTM model, a BERT model, a ChatGPT model, etc. In some embodiments, the inquiry model may include a missing information determination model and a first inquiry content determination model. The missing information determination model is configured to output missing information by processing known information about the doctor's department and the patient. The first inquiry content determination model is configured to output inquiry content based on the patient's missing information.

[0321] Step 1420: Based on the inquiry content, control the patient terminal to conduct a pre-diagnosis inquiry on the patient.

[0322] In some embodiments, after a patient registers with a doctor, the processing device 210 can determine the estimated waiting time for the patient to receive medical consultation services. For example, the estimated waiting time could be the time difference between the current moment and the patient's registration time. Alternatively, the estimated waiting time could be determined based on the doctor's daily consultation record and the patient's registration record. The doctor's daily consultation record is a record reflecting the doctor's outpatient activities that day.

[0323] In some embodiments, in response to determining that the estimated waiting time is greater than a first preset time threshold, the processing device 210 can enable the patient's patient terminal to initiate a pre-consultation inquiry or display a suggestion to conduct a pre-consultation. This approach ensures sufficient time for the pre-consultation and avoids the doctor calling the patient during the pre-consultation process.

[0324] In some embodiments, in response to determining that the estimated waiting time is less than a second preset time threshold, the processing device 210 can enable the patient's terminal to initiate a pre-consultation inquiry or display a suggestion to conduct a pre-consultation inquiry to the patient. The second preset time threshold may be greater than a first preset time threshold. For example, when it is detected that the current time is less than 24 hours away from the registration period (i.e., the estimated waiting time is less than 24 hours), the patient terminal can display a suggestion to conduct a pre-consultation inquiry to the patient (e.g., by using a virtual avatar to make the suggestion), thereby promptly reminding the patient to conduct a pre-consultation inquiry.

[0325] In some embodiments, the processing device 210 can detect when a patient initiates a pre-consultation inquiry request through a patient terminal, and then enable the patient's patient terminal to conduct a pre-consultation inquiry on the patient.

[0326] In some embodiments, the patient terminal may present a virtual avatar for pre-consultation based on the inquiry content. The virtual avatar refers to a digital person with specific characteristics (e.g., specific appearance features, voice features, etc.) that can communicate with the patient for pre-consultation. Specifically, the processing device 210 can display the virtual avatar on the screen of the patient terminal (e.g., an XR device) and play the inquiry content through the patient terminal's audio output device. Simultaneously, the virtual avatar can simulate human language expressions, gestures, etc., providing the patient with a realistic communication experience. In some embodiments, the virtual avatar can be a visual representation of the pre-consultation intelligent agent.

[0327] In some embodiments, the virtual character may have preset physical characteristics. In some embodiments, the physical characteristics of the virtual character may be determined based on optical image data of the doctor who registered the patient. In some embodiments, the physical characteristics of the virtual character may be determined based on the patient's basic information. In some embodiments, the processing device 210 may select a suitable virtual character from a virtual character library as the virtual character based on the doctor's physical characteristics and / or the patient's basic information.

[0328] In some embodiments, the pre-consultation inquiry may include multiple rounds of questioning. The pre-consultation content may include the content of each round of questioning in the pre-consultation inquiry, and the pre-consultation inquiry can be conducted through... Figure 14B The process 1400B shown is executed.

[0329] like Figure 14B As shown, for the first round of query, the processing device 210 can enable the patient terminal to perform the first round of query based on the corresponding query content.

[0330] For each current round of questioning (excluding the initial question), the processing device 210 can adjust the content of the current question (hereinafter referred to as the current question content) based on reference data collected before the current question, so that the question content is more in line with the patient's condition. Specifically, the processing device 210 can determine the semantic and emotional information of the patient's historical responses based on the reference data collected before the current question. The reference data may include voice signals, image data, text data, etc., collected from the patient's terminal. Historical responses are the patient's answers to the questions in previous rounds.

[0331] The semantic information of historical responses represents the content of those responses. The emotional information of historical responses can indicate the patient's emotions at the time of providing those responses (e.g., calm, tense, anxious, fearful, doubtful, irritable, etc.). Processing device 210 can determine semantic information by performing text transcription, speech content recognition, etc., on the reference data. Processing device 210 can determine emotional information by analyzing features such as the content, tone, intonation, and speech rate of the reference data.

[0332] Continue to refer to Figure 14B The processing device 210 can adjust the current inquiry content based on semantic and emotional information. For example, when the patient's emotional information is "nervous" or "fearful," the processing device 210 can add reassuring words to the current inquiry content. Similarly, when semantic information indicates that the patient has not clearly answered previous inquiries, the processing device 210 can adjust the current inquiry content to repeat the previous inquiries, thereby guiding the patient to provide clear answers. The originally determined current inquiry content can be used as the content for the next round of inquiries. This allows for timely adjustment of the current consultation content based on the patient's condition, thereby improving the quality of pre-consultation services.

[0333] In some embodiments, in addition to adjusting the current question content, the voice features used for the questioning can be adjusted in real time based on the patient's condition. Voice features include speech rate features, tone features, intonation features, volume features, etc. Figure 14B As shown, the processing device 210 can determine the voice characteristics of the current inquiry based on the semantic and emotional information of the patient's historical responses, and enable the patient terminal to adjust the current inquiry based on the adjusted inquiry content and the voice of the current inquiry. This method can better cater to the patient's emotional changes, thereby enhancing the anthropomorphic effect of the virtual character and improving the quality of pre-diagnosis services.

[0334] In some embodiments, such as Figure 14BAs shown, the processing device 210 can further acquire the patient's physiological state information. This physiological state information reflects the patient's real-time physiological state. It may include the patient's physiological parameter values ​​(e.g., heart rate, pulse rate, respiratory rate, etc.). The physiological state information may also include information related to the patient's posture, limb behavior, facial expressions, muscle state, etc. In some embodiments, the patient's physiological state information can be obtained through wearable devices worn by the patient or image sensors in the patient's environment.

[0335] Furthermore, the processing device 210 can adjust the current inquiry content based on semantic information, emotional information, and physiological state information. Specifically, the processing device 210 can update the patient's emotional information based on the patient's physiological state information. It is understood that a patient's inner emotions may not always be fully expressed through their answers; therefore, the patient's emotional information may be updated or modified based on the patient's physiological state information. In addition, the processing device 210 can adjust the current inquiry content based on semantic information and updated emotional information.

[0336] In some embodiments of this specification, by further considering the patient's physiological state data, the accuracy of the patient's emotional information can be improved, thereby improving the accuracy of adjusting the current inquiry content and thus improving the service quality of the pre-consultation service.

[0337] like Figure 14B As shown, in some embodiments, the processing device 210 can determine feedback parameters based on at least a portion of semantic information, emotional information, and physiological state information, and control the wearable device to apply feedback to the patient according to the feedback parameters. Feedback may include at least one of force feedback or temperature feedback. Feedback parameters can be used to control the manner in which feedback is applied, such as the type of feedback, the body part to which feedback is applied, and the intensity of feedback. In some embodiments, the processing device 210 can determine the patient's mood and mood level based on at least a portion of semantic information, emotional information, and physiological state information, and determine feedback parameters based on the mood and mood level. This method can promptly soothe the patient's negative emotions, thereby improving the quality of pre-consultation services.

[0338] In some embodiments, the processing device 210 may terminate the pre-consultation inquiry based on preset conditions. The preset conditions may include a remaining amount of missing information being zero. Alternatively, the preset conditions may include a time difference between the patient's current time and the estimated waiting time being less than a threshold.

[0339] In some embodiments, the inquiry content determined in step 1410 may only include the inquiry content of the first round of inquiries. The current inquiry content for each current inquiry in addition to the first round of inquiries can be determined during the pre-consultation inquiry process. For example, in the current inquiry, the processing device 210 can input the inquiry content of historical inquiries, the patient's historical answers, the patient's known information, etc., into the second inquiry content determination model, and the second inquiry content determination model outputs the current inquiry content.

[0340] Step 1430: Generate a pre-consultation record based on the reference data collected by the patient terminal during the pre-consultation inquiry.

[0341] Reference data may include voice data, text data, and image data input by the patient through their terminal during the pre-consultation. The pre-consultation record can be used to record patient information collected during the pre-consultation. Optionally, some known information about the patient may also be recorded in the pre-consultation record. In some embodiments, the pre-consultation record is generated according to a pre-consultation record template. The pre-consultation record template may be a template corresponding to the doctor's department, or it may be a template set by the doctor.

[0342] For example, when the reference data includes speech signals, the processing device 210 can first transcribe the speech signals into text and extract keywords from the text using a keyword extraction algorithm. Furthermore, the processing device 210 can convert the keywords into medical terminology. Additionally, the processing device 210 can obtain multiple template fields from the pre-consultation record template, retrieve the content corresponding to each template field from the medical terminology, and fill it into the corresponding position in the pre-consultation record template. Keyword conversion can be performed based on a terminology conversion model or a knowledge dictionary. The terminology conversion model can be configured to convert spoken descriptions into medical terminology.

[0343] In some embodiments, the pre-consultation inquiry can be performed via a terminal device other than the patient's terminal (e.g., a waiting terminal).

[0344] Figure 15 This is a schematic diagram of an exemplary process for providing medical outpatient services based on perceived information, according to some embodiments of this specification. The diagram illustrates a medical consultation service. In some embodiments, process 1500 may include one or more of sub-processes 1510, 1520, 1530, and 1540. In some embodiments, at least a portion of process 1500 is executed by a consultation agent configured on processing device 210 corresponding to the medical consultation service.

[0345] During the consultation process, patients can communicate with the registered doctor to receive consultation services (e.g., in-person consultation in the examination room, remote consultation). In some embodiments, user services related to the consultation process can be provided to relevant users (e.g., doctors, patients, remote companions) through at least one terminal device. At least one terminal device includes a public terminal device in the examination room, a patient terminal device, a doctor terminal device, and a terminal device for the remote companion. A public terminal device in the examination room refers to a terminal device installed in the examination room, which may include display devices, sound output devices, sound sensors, XR devices, wearable devices, etc., or any combination thereof. Sensing information can be collected during the consultation process by sensing devices in the environment where the patient, doctor, or remote companion is located. Sensing devices can be standalone devices or part of at least one terminal device.

[0346] Sub-process 1510 can be used to provide consultation suggestions based on perceived information. Sub-process 1510 can be executed during the consultation process. Figure 15 As shown, subprocess 1510 may include steps 1512 and 1514.

[0347] Step 1512: Generate consultation suggestions based on perceived information and the patient's patient data. Consultation suggestions refer to recommendations that assist doctors in providing medical consultation services. For example, consultation suggestions may include suggestions for supplementary inquiries, physical examinations, prescriptions, and treatment plans.

[0348] In some embodiments, consultation recommendations can be determined based on a knowledge database corresponding to the registered department, consultation guidelines, etc. For example, processing device 210 can determine the content of the conversation between the doctor and the patient based on the voice signal collected by the sound sensor, and search the knowledge database, consultation guidelines, etc., based on the conversation content and / or patient data to determine consultation recommendations. As an example only, the consultation guidelines can be searched based on the conversation content and / or patient data to determine which information in the consultation guidelines has not yet been collected, and supplementary inquiry suggestions can be provided based on this information.

[0349] In some embodiments, consultation suggestions can be generated based on a diagnostic model. Specifically, the processing device 210 can determine the model input based on perceived sensory information and patient data, input the model input into the diagnostic model, and the diagnostic model can output corresponding consultation suggestions. For example, the model input may include patient data, dialogue content determined based on speech signals, patient status information determined based on image data, or any combination thereof.

[0350] In some embodiments, consultation recommendations can be generated by a consultation agent. The consultation agent can learn a mechanism for generating consultation recommendations from various data (e.g., historical consultation records, knowledge databases, and consultation guidelines), and process perceived information and patient data according to this mechanism to provide consultation recommendations.

[0351] Step 1514: Control at least a portion of at least one terminal device to present consultation recommendations.

[0352] For example, when a patient receives in-person medical consultation services in a clinic, the processing device 210 can control a public terminal device or a doctor's terminal to present consultation suggestions. Similarly, when a patient receives telemedicine consultation services, the processing device 210 can control both the doctor's terminal and the patient's terminal to present consultation suggestions. Consultation suggestions can improve the accuracy of diagnoses and prescriptions, and increase the efficiency of medical consultation services.

[0353] Sub-process 1520 can be used to generate a target diagnostic record based on perceived information. Sub-process 1520 can be executed at the end of the consultation phase. Figure 15 As shown, subprocess 1520 may include steps 1522, 1524 and 1526.

[0354] Step 1522: Generate an initial diagnostic record based on the perceived information.

[0355] The initial diagnostic record can be an automatically generated diagnostic record. In some embodiments, the initial diagnostic record may include the initial patient medical record, initial diagnostic opinion, initial diagnostic prescription (e.g., initial treatment prescription and initial examination prescription), initial medical orders, etc. In some embodiments, key content can be extracted from perceived information based on a diagnostic record template. Key content refers to content related to template fields in the diagnostic record template. Key content can be converted into professional content based on a knowledge dictionary or terminology conversion model. Furthermore, the diagnostic record template can be updated based on professional content and a knowledge database to generate the initial diagnostic record. The knowledge database refers to the knowledge database of the registered department, for example, including the department's consultation guidelines (e.g., disease description guidelines, diagnostic guidelines, prescription guidelines, medical order guidelines, etc.).

[0356] In some embodiments, physical examination data of patients collected by one or more examination devices during an outpatient process can be acquired, and an initial diagnostic record can be further generated based on the physical examination data. In some embodiments, the initial diagnostic record can be generated by a consultation agent. The consultation agent can learn the mechanism for generating diagnostic records from various data (e.g., diagnostic record templates, knowledge dictionaries, knowledge databases, etc.), and process perceived information and patient data according to the learned mechanism to generate diagnostic records.

[0357] Step 1524: Present the initial diagnostic record to the doctor.

[0358] For example, when a patient begins a consultation, processing device 210 can control a public terminal to present an initial diagnostic record. As another example, processing device 210 can control a doctor's terminal to present an initial diagnostic record to the doctor. In some embodiments, the doctor's terminal can present the initial diagnostic record to the doctor at a preset time (e.g., after the doctor has finished their consultations for the day).

[0359] Step 1526: Generate the target diagnostic record based on the initial diagnostic record and the feedback information entered by the doctor on the initial diagnostic record.

[0360] The feedback information entered by the physician may include modifications and / or confirmations of the initial diagnostic record. A target diagnostic record refers to a diagnostic record modified and / or confirmed by the physician. In some embodiments, a target diagnostic record may include a target patient's medical record, a target diagnostic opinion, a target diagnostic prescription (e.g., a target treatment prescription and a target examination prescription), target medical orders, etc.

[0361] By generating targeted diagnostic records, on the one hand, we can reduce manual errors in generating these records and improve efficiency. On the other hand, we can reduce doctors' paperwork, allowing them to focus more on patient care and thus improving the quality of outpatient medical services.

[0362] Sub-process 1530 can be used to provide remote companionship services based on perceived information. Patients can initiate a request for remote companionship services before the consultation. Sub-process 1530 can be executed during the consultation process. Figure 15 As shown, subprocess 1530 may include steps 1532 and 1534.

[0363] Step 1532: Based on the perceived information, determine whether the patient needs to communicate with the remote companion.

[0364] In some embodiments, the processing device 210 can detect whether a patient has requested to communicate with a remote companion based on perceived information (e.g., voice data and / or image data). In some embodiments, the processing device 210 can determine the patient's state information based on the perceived information and determine whether the patient needs to communicate with a remote companion based on the patient's state information. For example, when the state information indicates that the patient is in a state of high tension, fear, etc., the processing device 210 can determine that the patient needs to communicate with a remote companion.

[0365] When it is determined that the patient needs to communicate with a remote companion, the processing device 210 can perform step 1534.

[0366] Step 1534: Control at least a portion of at least one terminal device to enlarge interface elements.

[0367] When a patient receives in-person medical consultation in the clinic, the processing device 210 can control the public terminal device to magnify its interface elements. When a patient receives remote medical consultation, the processing device 210 can control the patient's terminal to magnify its interface elements. Through the magnified interface elements, the patient can view the real-time video feed of the remote companion and better communicate with them.

[0368] In some embodiments, when a patient is receiving on-site medical consultation services in a consultation room, and when it is detected that the patient needs to communicate with a remote companion, the processing device 210 can remind the patient to wear an XR device and control the XR device to display the image data of the remote companion.

[0369] In some embodiments of this specification, the patient's communication needs can be detected based on sensory information and these needs can be met in a timely manner, thereby providing the patient with more humane care and a more realistic and immersive companionship experience.

[0370] Subprocess 1540 can be used to present medical data to target users based on perceived information. For example... Figure 15 As shown, subprocess 1540 may include steps 1542 and 1544.

[0371] Step 1542: Based on the perceived information, obtain control commands issued by at least one target user for retrieving at least a portion of medical data.

[0372] Target users can include at least patients and doctors. In some embodiments, target users may also include remote companions to the patient. Patient medical data may include various data reflecting the patient's health status (e.g., electronic medical records, medical images, medical examination results, etc.).

[0373] Control instructions are instructions used to retrieve and display at least a portion of medical data (e.g., electronic medical records). For example, control instructions may be used to retrieve and display a 3D model of a patient's organ of interest from an electronic medical record. In some embodiments, control instructions may be used to set display parameters (such as display angle, display size, or display position). In some embodiments, control instructions may also be used to annotate key data on the medical data (e.g., the 3D model of the organ of interest).

[0374] In some embodiments, the perception information may include voice signals acquired by a sound sensor, and control commands may be obtained by performing semantic analysis on the voice signals. In some embodiments, the target user may issue control commands by uttering a preset wake word. In some embodiments, the perception information may include optical image data of the target user (e.g., a patient and / or doctor) acquired by an image sensor, and control commands may be obtained by recognizing gestures of the target user in the optical image data. In some embodiments, the target user may issue control commands using a control device (e.g., a remote control, smart control gloves, etc.).

[0375] In some embodiments of this specification, the target user can flexibly adjust the displayed content and / or display parameters, for example, through voice, gestures, etc., thereby optimizing the user experience and improving the efficiency of medical consultation services.

[0376] Step 1544: In response to a control command, at least a portion of the medical data is retrieved and presented through at least one terminal device.

[0377] For example, processing device 210 can retrieve at least a portion of medical data from storage device and control at least one terminal device to present at least a portion of the medical data. When the control instruction includes display parameters, processing device 210 can control at least one terminal device to present at least a portion of the medical data based on the display parameters.

[0378] In some embodiments of this specification, multiple target users can browse medical data together through at least one terminal device, and can synchronously change the presentation content and presentation method of medical data on different terminal devices. This helps to improve the communication efficiency of target users and enhance the interactivity of the medical treatment process.

[0379] Figure 16 This is a schematic diagram illustrating an exemplary process for providing services to relevant users during the admission process, according to some embodiments of this specification. During the admission process, patients can complete the necessary procedures for admission. In some embodiments, at least a portion of process 1600 is performed by an inpatient agent corresponding to an inpatient service configured on processing device 210. In some embodiments, at least a portion of process 1600 (e.g., steps 1630-1650) is performed by a nursing agent corresponding to a nursing service configured on processing device 210.

[0380] In step 1610, the treatment device 210 can guide the patient to the ward.

[0381] For example, processing device 210 can instruct the patient's terminal to guide the patient to a ward. For instance, in response to a hospitalization guidance request, processing device 210 can obtain the first location of the patient's terminal and the second location of the ward, and determine a planned route from the first location to the second location based on a real-time map of the hospital. Then, processing device 210 can instruct the patient terminal to present guidance information related to the planned route to the patient.

[0382] Step 1620: Provide admission education information to the patient.

[0383] Hospital admission education information can be used to introduce patients to admission information (e.g., admission procedures, admission processes, pre-admission fees, payment methods, etc.), admission and hospitalization rules, hospital environment, and the patient's doctor and / or nurse. In some embodiments, the processing device 210 can cause the patient terminal device (e.g., XR device 260-2) to display a virtual character providing hospital admission education information.

[0384] In 1630, the processing device 210 can assist nurses in preparing for admission.

[0385] Admission preparation can be performed by nurses, who prepare hospital supplies for the patient. In some embodiments, the processing device 210 can present the patient's admission notification via a nurse's workstation or a nurse terminal 1605 in a smart nursing cart 240-4 to assist nurses in performing admission preparation. The admission notification may include the patient's patient data, a list of the patient's hospital supplies, the patient's ward information, the patient's initial examination information, etc.

[0386] Admission examinations, also known as inpatient examinations, are performed after a patient is admitted to their ward. Admission examinations are used to gather information about the patient's current medical condition (e.g., vital signs, basic health data). Initial examinations may include blood pressure, blood glucose, heart rate, body temperature, or similar tests, or any combination thereof.

[0387] In step 1640, the processing device 210 may issue a reminder to perform admission examinations. The reminder may include a message reminder, an audio reminder, a pop-up reminder, etc. For example, the processing device 210 may instruct the nurse terminal 1605 or the smart nursing cart 240-4 to display the reminder.

[0388] In some embodiments, the processing device 210 can determine whether a patient meets the criteria for admission examination in the ward based on sensing information collected by sensing devices in the ward. The criteria for admission examination in the ward may include that the patient has been in the ward for a period of time. If the patient meets the criteria, the processing device 210 can issue a reminder to proceed with the admission examination.

[0389] In step 1650, the processing device 210 can guide the nurse to the ward. In some embodiments, the processing device 210 can control the movement of the intelligent nursing cart 240-4 to guide the nurse into the ward.

[0390] Step 1660: Conduct admission examinations on the patient.

[0391] For example, after a nurse arrives at the ward, one or more examination devices can be used to conduct an admission examination on the patient to collect the patient's physical examination data. In some embodiments, after the smart nursing cart arrives at the ward, the processing device 210 can instruct the smart nursing cart to present information related to the admission examination to the nurse during the admission examination. For example, the smart nursing cart can present admission examination diagrams, the patient's electronic medical record, etc.

[0392] Step 1670: Processing device 210 generates admission record.

[0393] An admission record is a record showing that a patient has been admitted to a ward and / or the patient's status at the time of admission. Admission records may include admission information (e.g., admission number, clinical information, admission time, prepaid hospital fees, payment method, etc.) and physical examination data collected during admission examinations.

[0394] In some embodiments, the processing device 210 can generate an admission record based on an admission record template and physical examination data. In some embodiments, the processing device 210 can further generate an admission record based on the patient's electronic medical record. In some embodiments, the processing device 210 can present the admission record to the nurse based on the intelligent nursing cart 240-4 or the nurse terminal 1605, and generate a target admission record based on the admission record and feedback information entered by the nurse through the intelligent nursing cart 240-4 or the nurse terminal 1605. The feedback information may include confirmation instructions, modification instructions, etc., entered by the nurse.

[0395] In some embodiments of this specification, patient admission services can be provided in a semi-automatic manner with the assistance of a medical service system (e.g., intelligent nursing cart 240-4) and / or intelligent agents, thereby reducing labor costs and improving the efficiency of admission services.

[0396] Figure 17 This is a schematic diagram illustrating a process for providing nursing services according to some embodiments of this specification. In some embodiments, process 1700 may be performed daily during a patient's hospitalization to provide nursing services. In some embodiments, at least a portion of process 1700 may be performed by a hospitalization agent corresponding to a hospitalization service configured on processing device 210. In some embodiments, at least a portion of process 1700 may be performed by a nursing agent corresponding to a nursing service configured on processing device 210.

[0397] Step 1702: The processing device 210 determines the patient's daily schedule based on the patient's data and the doctor's orders.

[0398] A doctor's orders to a patient refer to instructions or directives given by a doctor to the patient. In some embodiments, the patient's orders can be stored in a storage device and updated whenever a doctor issues a new order to the patient. Processing device 210 can retrieve the latest version of the orders from the storage device. In some embodiments, processing device 210 can monitor various hardware devices to detect whether the patient's orders have been updated. For example, when providing admission inquiry services and / or ward rounds to a patient, the patient's doctor may issue a new order. Processing device 210 can detect the new order based on sensing information collected by sensing devices during the admission inquiry service and / or ward rounds. Once a new order is detected, it can be stored in the storage device. As another example, a doctor can update the orders in the storage device via a doctor's terminal. In some embodiments, processing device 210 can determine the doctor's orders based on the patient's electronic medical record.

[0399] In some embodiments, the processing device 210 can determine a patient's daily schedule based on the patient's patient data and medical orders. The daily schedule may include at least one medical procedure that needs to be performed on the patient that day. Exemplary medical procedures may include nursing procedures, examinations, etc.

[0400] In step 1704, the processing device 210 can present the daily schedule to the patient through a public terminal device in the ward (e.g., bedside terminal 240-6).

[0401] In step 1706, the processing device 210 can present the daily plan to the nurse corresponding to the patient through a nurse terminal (e.g., a terminal device in a nurse workstation).

[0402] Step 1708: When the daily plan includes at least one nursing procedure, the nurse may perform at least one nursing procedure on the patient, and the processing device 210 may assist the nurse in performing at least one nursing procedure according to the daily plan.

[0403] like Figure 17 As shown, for each of at least one nursing procedure, the processing device 210 can control the smart nursing cart to guide the nurse to the patient's ward to perform the procedure according to the scheduled time of the nursing procedure. For example, before the scheduled time of the nursing procedure, the smart nursing cart can be controlled to move to the nurse's workstation to notify the nurse that a nursing procedure needs to be performed on the patient. Then, the smart nursing cart can be controlled to move and guide the nurse to the patient's ward. The processing device 210 can further control the smart nursing cart to display nursing instructions related to the nursing procedure after the nurse arrives at the ward.

[0404] In step 1710, the processing device 210 can generate a nursing record.

[0405] A nursing record is a record of nursing procedures applied to a patient and / or their condition (e.g., vital signs and other physiological measurements) before, after, or during a nursing procedure. In some embodiments, the processing device 210 may acquire sensory information collected by one or more sensing devices in the ward while performing at least one nursing procedure and generate a nursing record based on that sensory information. In some embodiments, the nursing record may be displayed to a nurse for confirmation via a smart nursing cart or a nurse terminal device.

[0406] In some embodiments of this specification, the automated generation of daily plans and nursing records can significantly reduce the workload of nurses. This automation allows nurses to focus more on direct patient care rather than administrative tasks. Furthermore, monitoring of updated medical orders ensures timely updates to daily plans. This proactive approach ensures that interventions and nursing plans are adjusted promptly based on the latest medical orders, thereby improving nursing outcomes and quality.

[0407] Figure 18 This is an exemplary schematic diagram of a preoperative guidance process according to some embodiments of this specification. In some embodiments, at least a portion of process 1800 may be executed by a surgical agent corresponding to a surgical service configured on processing device 210.

[0408] Preoperative instructions may include patient transport, patient confirmation, preoperative education, preoperative cleaning, and establishment of intravenous access. Patient transport refers to moving the patient from his / her current location to the waiting area of ​​the operating room.

[0409] Patient verification refers to verifying whether a patient meets the surgical criteria. For example, patient verification may include: verifying whether the verification subject's identity information matches the target patient for the current surgical procedure; verifying whether the verification subject's surgical schedule is currently available; and verifying whether the verification subject's current physical condition meets the requirements of the surgical procedure. Understandably, if the verification subject does not meet any of the surgical criteria, the patient's surgical schedule may be postponed or delayed.

[0410] In some embodiments, the processing device 210 may collect the patient's biometric information through one or more sensing devices in the waiting area and verify the patient's identity based on the biometric information. For example, such as Figure 18As shown, after a patient is transported to waiting area 1810, processing device 210 can collect the patient's biometric information through one or more sensing devices 1811 (e.g., image acquisition devices, microphones, fingerprint sensors, etc.) in waiting area 1810, and verify the patient's identity based on the biometric information. In some embodiments, processing device 210 can utilize a nurse agent to verify the patient's identity. For example, the nurse agent can verify the collected biometric information, or verify the patient's identity through voice interaction with the patient (e.g., asking the patient's age, name, gender, etc.).

[0411] Preoperative care can include preoperative reassurance and preoperative education. Preoperative reassurance refers to preoperative preparation, using methods such as verbal communication, videos, and music to help patients reduce negative emotions (e.g., anxiety, tension, fear). Preoperative education refers to preoperative preparation, helping patients understand the surgical procedure. Preoperative cleaning refers to preoperative preparation, such as body cleaning, hair removal (e.g., hair, body hair), and dressing the patient in surgical gowns. Establishing intravenous access refers to establishing intravenous access in the patient to administer medication, ensuring that drugs are effectively delivered to the patient during surgery.

[0412] In some embodiments, the processing device 210 can determine a planned path from the patient's current location to the waiting area and control the smart wheelchair to transport the patient to the waiting area along the planned path. For example, as Figure 18 As shown, before performing preoperative procedures on the patient according to the surgical plan, the processing device 210 can determine a planned path from the patient 261's current location (e.g., ward 1803) to the waiting area 1810. The processing device 210 can control the intelligent wheelchair 240-5 to transport the patient 261 from ward 1803 to the waiting area 1810 along the planned path.

[0413] In some embodiments, the processing device 210 may determine a planned route from the current location to the waiting area based on a hospital map. In some embodiments, the processing device 210 may configure a nurse agent that performs certain tasks on behalf of a nurse and may present a virtual nurse persona. The processing device 210 may use the nurse agent to control a smart wheelchair to transport the patient from the current location to the waiting area. In some embodiments, after transporting the patient to the waiting area, the processing device 210 may perform patient verification.

[0414] In some embodiments, the processing device 210 can determine preoperative care materials for the patient based on patient data and surgical plans. During patient transport to the waiting area, the processing device 210 can use a patient terminal to provide preoperative education to the patient based on the preoperative care materials. Preoperative care materials may include videos, music, images, text, and other relevant materials such as surgical explanations and / or relaxation techniques.

[0415] In some embodiments, the processing device 210 may use a nurse agent to provide preoperative education to patients. For example, such as Figure 18 As shown, the processing device 210 can display a virtual nurse character 1823 on the XR device 260-2 worn by the patient 261. The virtual nurse character 1823 explains preoperative nursing materials to the patient 261. In some embodiments, the virtual nurse character 1823 can interact with the patient 261 via voice to alleviate the patient's negative emotions or answer the patient's questions through communication. In some embodiments, the processing device 210 can determine whether it is necessary to alleviate the patient's emotions by collecting the patient's facial expressions, physiological signs, tone of voice, etc.

[0416] In some embodiments, the processing device 210 may use a nurse agent to instruct nurses to perform preoperative cleaning and / or establish intravenous access.

[0417] In some embodiments, during the transport of a patient to a waiting area, the processing device 210 can acquire sensing information related to a portion of the planned path from the current location of the smart wheelchair to the waiting area (e.g., a portion of the planned path that the smart wheelchair has not yet traveled) via one or more sensing devices in the hospital. Based on the sensing information, the processing device 210 can determine potential risks in the untraveled portion of the planned path and update the untraveled portion based on the potential risks.

[0418] One or more sensing devices may include image acquisition devices (e.g., infrared surveillance camera 1813), lidar, etc. These sensing devices may be installed in locations such as smart wheelchairs, hospital ceilings, or hospital walls.

[0419] In some embodiments of this specification, the preoperative guidance process described above provides a humanized, transparent, and efficient preoperative preparation process. Preoperative preparation items can be dynamically adjusted based on patient feedback, improving efficiency. The patient transport and identity verification processes described above avoid human error and enhance the safety of the entire surgical procedure. Utilizing virtual nurse images to assist in many preoperative preparation tasks can save labor costs.

[0420] Figure 19 This is a schematic diagram of a surgical execution flow according to some embodiments of this specification. The surgical execution flow 1900 may include preoperative preparation, intraoperative matters, and postoperative matters. In some embodiments, at least a portion of the flow 1900 may be executed by a surgical agent corresponding to a surgical service configured on the processing device 210. For example... Figure 19 As shown, preoperative preparation (e.g., steps before surgery) may include steps 1911, 1913, and 1915.

[0421] Step 1911: Activate the operating room.

[0422] Activating the operating room may include opening the operating room door, activating surgical equipment and monitoring equipment within the operating room, adjusting parameters within the operating room, and verifying the status of the surgical equipment. In some embodiments, the processing device 210 may control the intelligent robot nurse to activate the operating room or guide the nurse to activate the operating room. For example, the processing device 210 may control the intelligent robot nurse to automatically start the operating room equipment at a predetermined time for the surgery and adjust the indoor temperature, humidity, and air quality.

[0423] Step 1913: Prepare surgical instruments.

[0424] Surgical tools may include surgical instruments and surgical consumables. In some embodiments, the processing device 210 may control an intelligent robotic nurse to prepare surgical tools in the operating room before surgery, according to the surgical plan. In some embodiments, the processing device 210 may further control the intelligent robotic nurse to sterilize and arrange the operating table (e.g., to position various surgical tools on the operating table).

[0425] Step 1915, Patient Confirmation and / or Patient Anesthesia. Patient confirmation refers to confirming the patient's identity. Patient anesthesia refers to administering anesthesia to the patient.

[0426] Step 1920: Perform the surgical procedure. In some embodiments, such as... Figure 19 As shown, matters during the surgical procedure (e.g., intraoperative matters) may include remote collaboration, tool transfer, image interaction, intraoperative planning and navigation, and real-time alerts.

[0427] Remote collaboration refers to remote participation and / or remote guidance during the surgical procedure.

[0428] Tool delivery refers to the handing over of surgical tools to the surgical practitioner during surgery. In some embodiments, processing device 210 can identify instructions issued by the surgical participant for a target surgical tool based on first sensing information collected by one or more first sensing devices in the operating room during surgery. Based on these instructions, processing device 210 can control an intelligent robotic nurse to deliver the target surgical tool to the surgical participant.

[0429] Image interaction refers to displaying a digital human body model of the patient (e.g., a three-dimensional anatomical model of the surgical site), the patient's electronic medical record, the surgical plan for the current operation, real-time images of the patient's surgical site, etc., to surgical participants (e.g., local surgical participants, remote surgical participants) and / or the patient through interactive devices in the operating room (e.g., displays in the operating room, doctor's terminal device 270).

[0430] Intraoperative planning and navigation refers to the process of fusing images of the patient's lesion (e.g., CT scan images of the lesion) with the patient's digital human model during surgery, projecting the lesion image onto the patient's body, or overlaying the positioning and tracking of surgical tools to guide surgical participants in the operation.

[0431] Real-time alarms can include behavioral alarms for surgical participants, patient vital sign alarms, and equipment status alarms. Behavioral alarms refer to the monitoring and alerting of surgical participants' intraoperative actions. Patient vital sign alarms can be activated when abnormalities occur in the patient's vital signs (e.g., electrocardiogram, blood pressure, etc.). Equipment status alarms are alerts issued when surgical equipment malfunctions.

[0432] like Figure 19 As shown, the post-operative process (e.g., post-operative matters) may include steps 1931, 1933 and 1935.

[0433] Step 1931, Transferring the Patient. Transferring the patient refers to the process of moving the patient from the operating room to the recovery area after the surgical procedure is completed. In some embodiments, the transfer may be performed by healthcare professionals assisted by a robotic nurse.

[0434] Step 1933: Perform operating room cleaning. Operating room cleaning refers to the process of cleaning or disinfecting surgical equipment and tools. In some embodiments, the processing device 210 may control an intelligent robotic nurse to perform operating room cleaning.

[0435] Step 1935: Generate the surgical report.

[0436] The surgical report may include surgical-related information, patient-related records, participant-related records, etc. In some embodiments, the processing device 210 can generate an initial surgical report based on data collected during the surgical procedure (e.g., sensory information collected by one or more sensing devices in the operating room). The processing device 210 can generate a surgical report based on the initial surgical report and feedback information input by the physician regarding the initial surgical report.

[0437] In some embodiments, the processing device 210 can also monitor the patient's postoperative vital signs using vital sign monitoring devices in the ward (e.g., electrocardiogram monitor, blood pressure monitor, etc.) to determine whether the patient's postoperative vital signs are within the normal range, whether there are any abnormalities, or whether the recovery progress is normal. Furthermore, the processing device 210 can update the medical recommendation report based on the patient's postoperative vital signs. In some embodiments, the processing device 210 can update the medical recommendation report according to the doctor's instructions. In some embodiments, the processing device 210 can send the updated medical recommendation report to the display device of the nurse's workstation and / or the display device of the doctor's workstation.

[0438] In some embodiments, the processing device 210 can determine a postoperative care plan based on updated medical advice reports. A postoperative care plan refers to the nursing tasks that need to be performed by caregivers (e.g., nurses, nursing assistants, etc.) during the patient's postoperative hospitalization. In some embodiments, the processing device 210 can control intelligent surgical equipment (e.g., intelligent nursing cart 240-4) to provide care to the patient according to the postoperative care plan. In some embodiments, the processing device 210 can send the postoperative care plan to a nurse so that the nurse can provide postoperative care to the patient. In some embodiments, the processing device 210 can update the postoperative care plan in real time according to the patient's condition during the care process. The execution of the postoperative care plan is similar to... Figure 17 The daily schedule described in the document.

[0439] In some embodiments, the processing device 210 can generate surgical results and surgical records for doctors based on surgical reports and medical advice reports, so that doctors can review the surgical process. Surgical results refer to data reflecting the outcome of the surgical procedure. In some embodiments, surgical results also include summary data of surgical results over a predetermined time period (e.g., one month). Surgical records refer to the doctor's operational records during the surgical process. Operational records may include action records, force records, positioning records, etc. In some embodiments, the processing device 210 can generate surgical results and surgical records based on surgical reports and medical advice reports.

[0440] In some embodiments, the surgical procedure can be reviewed. For example, processing device 210 can present the surgeon's surgical results and operational records to the surgeon, thereby allowing the surgeon to review the surgical procedure.

[0441] The basic concepts have been described above. Obviously, for those skilled in the art who have read this application, the above disclosure is merely illustrative and does not constitute a limitation of this application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this application. Such modifications, improvements, and corrections are suggested in this application, and therefore, such modifications, improvements, and corrections still fall within the spirit and scope of the exemplary embodiments of this application.

[0442] Furthermore, this application uses specific terms to describe embodiments of the application. For example, the terms "one embodiment," "an embodiment," and / or "some embodiments" may mean that a specific feature, structure, or characteristic related to an embodiment is included in at least one embodiment of this disclosure. Therefore, it should be emphasized and noted that "one embodiment," "an alternative embodiment," or "an alternative embodiment" mentioned twice or more in different places in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this application can be appropriately combined.

[0443] Furthermore, those skilled in the art will understand that aspects of this application can be described and illustrated in several patentable ways, including any new and useful combination of processes, machines, products, or substances, or any new and useful improvements thereof. Therefore, aspects of this disclosure can be implemented entirely in hardware, entirely in software (including firmware, resident software, microcode, etc.), or in a combination of software and hardware, all of which are generally referred to herein as “units,” “modules,” or “systems.” Furthermore, aspects of this disclosure can take the form of computer program products embodied in one or more computer-readable media having computer-readable program code.

[0444] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this application are not intended to limit the order of the processes and methods of this application. Although the foregoing disclosure has discussed some currently considered useful embodiments of the invention through various examples, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the substance and scope of the embodiments of this application. For example, while the implementation of the various components described above can be embodied in a hardware device, it can also be implemented as a purely software solution, for example, installed on an existing server or mobile device.

[0445] Similarly, it should be noted that, in order to simplify the description of the present application and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of the embodiments of the present application sometimes combines multiple features into a single embodiment, drawing, or description thereof. However, the method of the present application should not be construed as reflecting an intention that the claimed object to be scanned requires more features than expressly recited in each claim. Rather, the subject of the invention should possess fewer features than in any single embodiment described above.

[0446] In some embodiments, the numbers used to describe quantities or properties in the description and claims of certain embodiments of this application should be understood to be modified in certain circumstances by the terms "approximately," "approximately," or "substantially." For example, unless otherwise stated, "approximately," "approximately," or "substantially" may represent a variation of ±1%, ±5%, ±10%, or ±20% of the value described. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be varied depending on the characteristics required by the individual embodiment. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this application are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0447] Every patent, patent application, publication of a patent application, and other material such as articles, books, specifications, publications, documents, things, and / or similar materials cited herein are incorporated herein in their entirety by reference for all purposes, except for any related application archive history, any content inconsistent with or conflicting with this document, or any content that may limit the widest scope of the relevant claims present or thereafter. For example, if there is any inconsistency or conflict between the description, definitions, and / or use of terminology associated with any incorporated material and the terminology associated with this document, the terminology used in this document shall prevail.

[0448] Finally, it should be understood that the embodiments described in this application are merely illustrative of the principles of the embodiments of this application. Other modifications may also fall within the scope of this application. Therefore, alternative configurations of the embodiments of this application are considered as examples and not limitations, and are regarded as consistent with the teachings of this application. Accordingly, the embodiments of this application are not limited to the embodiments explicitly described and illustrated in this application.

Claims

1. A system for hospital management, characterized in that, The system includes: The administrator terminal is configured to present an interface for users to manage the hospital's intelligent agents, whereby the users are the hospital's administrators. The processing device is communicatively connected to the administrator terminal, wherein: The intelligent agent comprises software entities that are constructed and self-evolving based on artificial intelligence technology, and is implemented through the processing device. The interface is configured to present basic configuration data of the virtual character and the intelligent agent. The user manages the intelligent agent by interacting with the virtual character and querying and updating the basic configuration data. The basic configuration data refers to the key information that the intelligent agent relies on when providing services, and includes at least one of a dictionary, a knowledge database, and templates. The processing device is configured to receive updated basic configuration data input by the user via the interface from the administrator terminal, and to provide user services based on the updated basic configuration data using the intelligent agent.

2. The system according to claim 1, characterized in that, The interface is also configured to present operational metrics of the agent, including at least one of the following: the number of users served by the agent, the number of services provided by the agent, the amount of data processed by the agent, and the service quality of the agent.

3. The system according to claim 2, characterized in that, The interface includes a first display area and a second display area. The first display area is configured to display the basic configuration data of the intelligent agent, and the second display area is configured to display the operational indicators of the intelligent agent. The first display area and the second display area are displayed on the interface simultaneously.

4. The system according to claim 1, characterized in that, The intelligent agents include intelligent agents corresponding to different types of medical service providers, intelligent agents corresponding to different hospital departments, intelligent agents corresponding to different medical service processes, and intelligent agents corresponding to different user services.

5. The system according to claim 1, characterized in that, The intelligent agent includes a first intelligent agent corresponding to the medical service process, and the first intelligent agent is configured as follows: Monitor the updates of data related to the patient's healthcare service process; In response to the detection of data related to the healthcare service process, including updated data, Based on the updated data, perform the detection of events of interest; as well as In response to the detection of the event of interest, a preset operation corresponding to the event of interest is executed to provide user services to relevant users in the medical service process, wherein the detection of the event of interest and / or the preset operation are executed according to the updated basic configuration data corresponding to the first agent.

6. The system according to claim 5, characterized in that, The step of performing interest event detection based on the updated data includes: Determine the current stage of the patient's medical service process; Based on the patient's current state, determine the type of event of interest to be detected; and The detection of events of interest is performed on the updated data based on the type information.

7. The system according to claim 5, characterized in that, The step of performing interest event detection based on the updated data includes: Based on the hardware device corresponding to the updated data, determine the type information of the events of interest that need to be detected; and The detection of events of interest is performed on the updated data based on the type information.

8. The system according to claim 5, characterized in that, The detection of events of interest is based on rules for detecting events of interest, which are learned by the first agent from historical records and the updated basic configuration data.

9. The system according to claim 8, characterized in that, The rules for detecting events of interest are learned by the first agent from historical records, updated basic configuration data, and patient data.

10. The system according to claim 5, characterized in that, The preset operation corresponding to the event of interest is determined based on the correspondence between the event of interest and the preset operation, and the correspondence is learned by the first agent from the historical records and the updated basic configuration data.

11. The system according to claim 10, characterized in that, The correspondence is learned by the first agent from historical records, the updated basic configuration data, and the patient's patient data.

12. The system according to claim 1, characterized in that, The intelligent agent includes a second intelligent agent, which is used to implement user services related to various stages of the medical service process. The second intelligent agent is configured as follows: Acquire data related to the patient's described process; The data is processed based on the updated basic configuration data of the second intelligent agent; Based on the processing results, the user services are provided to the relevant users in the aforementioned process.

13. The system according to claim 12, characterized in that, The user services are obtained through user-space applications installed on the user terminal. The virtual character corresponding to the second intelligent agent is presented through a user space application. The user service is provided to the relevant user based on the interaction between the relevant user and the virtual character corresponding to the second intelligent agent.

14. The system according to claim 12, characterized in that, The second intelligent agent includes a pre-consultation intelligent agent corresponding to the pre-consultation service, and the pre-consultation intelligent agent is configured as follows: Based on the department of the doctor the patient registered with, a pre-diagnosis inquiry is conducted on the patient through the patient's patient terminal; The pre-consultation record is generated based on the data collected by the patient terminal during the pre-consultation inquiry.

15. The system according to claim 14, characterized in that, The pre-consultation process conducted by the doctor's department based on the patient's registration, through the patient's terminal, includes: Using an inquiry model, based on the doctor's department and patient information, the inquiry content is determined. The inquiry model includes an omission information determination model and a first inquiry content determination model. The omission information determination model is configured to output omission information by processing the doctor's department and patient information. The first inquiry content determination model is configured to output inquiry content based on the patient's omission information. Based on the content of the inquiry, the patient terminal is controlled to conduct a pre-diagnosis inquiry on the patient.

16. The system according to claim 14, characterized in that, The pre-consultation inquiry is based on the inquiry content and includes multiple rounds of inquiry. The inquiry content includes the content of each round of inquiry. The pre-consultation inquiry, based on the department of the doctor the patient registered with, is conducted on the patient's patient terminal and includes: For each round of pre-diagnosis questioning except for the first round of questioning, Based on the data collected before the current round of questioning, the semantic and emotional information of the patient's historical responses are determined; Based on the semantic information and the emotional information, the content of the current round of questions is adjusted; Based on the adjusted content of the current round of inquiries, the current round of inquiries is conducted through the patient terminal.

17. The system according to claim 14, characterized in that, The pre-consultation includes multiple rounds of questioning, and the pre-consultation questioning of the patient includes: For each current round of queries, excluding the first round of queries... Based on the content of historical inquiries, the patient's historical answers, and the patient's known information, an inquiry content determination model is used to determine the inquiry content corresponding to the current round of inquiries. The inquiry content determination model is a trained machine learning model. Based on the question content corresponding to the current round of questioning, the current round of questioning is conducted through the patient terminal.

18. The system according to claim 12, characterized in that, The second intelligent agent includes a consultation intelligent agent corresponding to the consultation service, and the consultation intelligent agent is configured as follows: During the patient's consultation process Based on the sensory information collected by the sensing device during the consultation, it is determined whether the patient needs to communicate with the remote companion. In response to determining that the patient needs to communicate with the remote companion, control at least one terminal device to zoom in on interface elements related to the remote companion service.

19. The system according to claim 12, characterized in that, The second intelligent agent includes an inpatient intelligent agent corresponding to inpatient services, and the inpatient intelligent agent is configured as follows: Based on the sensory information collected by the sensing devices in the ward, it is determined whether the patient meets the conditions for admission examination in the ward. In response to determining that the patient meets the admission examination criteria, the system controls the intelligent nursing cart to guide the nurse into the ward and controls the intelligent nursing cart to display information related to the admission examination. An admission record is generated based on the patient's physical examination data collected during the admission examination.

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