Hospital supporting platform

Abstract

The embodiment of the invention provides a hospital support platform, which comprises hardware equipment configured to acquire data related to hospital business; the data center comprises a data lake, and the data lake is configured to carry out persistent storage on the data in an anti-tampering mode; the processing equipment is provided with a data processing unit used for data processing, and the data processing unit comprises an augmented reality unit, an artificial intelligence unit, a digital twinborn body unit and a data circulation unit; and the user space application is configured for a related user of the hospital business to obtain a user service related to the hospital business, and the user service is realized by processing at least one part of the data stored in the data center by the processing equipment through utilizing at least one data processing unit.

Description

Cross-references

[0001] This application claims priority to international application No. PCT / CN2024 / 109064, filed on July 31, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This specification relates to the field of medical services, and in particular to a hospital support platform. Background Art

[0003] Medical business scenarios are usually complex. Although digital and information systems have been introduced into the medical industry, medical business involves many types of hardware equipment and huge data processing needs. In addition, the individual conditions of patients vary greatly, which means that providing efficient medical services still requires a lot of time, manpower and material resources. Especially in terms of information interaction between multiple departments, multiple systems and multiple medical institutions, the efficiency is usually low. Therefore, integrating and dispatching hardware and software resources inside and outside the hospital to effectively support medical services has become an urgent problem to be solved.

[0004] In addition, some problems that have long plagued the medical industry, such as difficulty in seeing a doctor, poor experience (such as long queues), shortage of medical staff, and high reliance on doctors' experience for diagnosis, still exist. Traditional medical data processing technology is usually only targeted at specific medical tasks and is difficult to meet the needs of complex and changing medical business scenarios.

[0005] Therefore, it is desired to provide a more reliable and efficient hospital support platform. Summary of the invention

[0006] One of the embodiments of the present specification provides a hospital support platform, including a hardware device configured to collect data related to hospital business; a data center, including a data lake, and the data lake is configured to persistently store the data in a tamper-proof manner; a processing device, configured with a data processing unit for data processing, the data processing unit including an extended reality unit, an artificial intelligence unit, a digital twin unit and a data circulation unit; a user space application, configured to provide users related to the hospital business with user services related to the hospital business, wherein the user service is implemented by the processing device using at least one of the data processing units to process at least a portion of the data stored in the data center.

[0007] In some embodiments, the system further includes a hardware and software interface configured to obtain the data from the hardware device and send the data to the data center for storage.

[0008] In some embodiments, obtaining the data from the hardware device and sending the data to the data center for storage includes: obtaining hardware configuration information of the hardware device, the hardware configuration information including a unique identity identifier; determining whether the hardware configuration information meets a preset condition; and in response to the hardware configuration information meeting the preset condition, sending the data to the data center for storage.

[0009] In some embodiments, the hardware configuration information also includes the operating status of the hardware device; determining whether the hardware configuration information meets the preset conditions includes: determining whether the hardware device is one of multiple trusted devices based on the unique identity identifier; and / or determining whether the hardware device is in a normal state based on the operating status of the hardware device.

[0010] In some embodiments, the system further includes an open interface configured to allow application developers to call at least a portion of the data processing unit and use the at least a portion of the data processing unit to develop applications.

[0011] In some embodiments, the hardware device includes an Internet of Things device and an extended reality device.

[0012] In some embodiments, the data center further includes a data warehouse configured to store an index of the data.

[0013] In some embodiments, the processing device is further configured to: determine evaluation information of the data; determine a storage strategy for the data based on the evaluation information; and store the data in the data lake based on the storage strategy.

[0014] In some embodiments, the evaluation information includes a combination of one or more of the security level of the data, the data volume and / or the data collection frequency, and the importance coefficient; determining the storage strategy of the data based on the evaluation information includes: in response to the security level corresponding to the data being higher than a preset security threshold, determining that the storage strategy of the data is to encrypt and store the data; and / or in response to the data volume and / or the data collection frequency being higher than a preset threshold, determining that the storage strategy of the data is to distribute and store the data; and / or determining the storage period of the data based on the importance coefficient of the data.

[0015] In some embodiments, the extended reality unit is configured to process the data using extended reality technology to realize extended reality services; the artificial intelligence unit is configured to process the data using artificial intelligence technology to realize artificial intelligence services; the digital twin unit is configured to process the data using digital twin technology to realize digital twin services; the data flow unit is configured to process the data using data flow technology to realize data flow services.

[0016] In some embodiments, at least a portion of the digital twin units are configured to call the extended reality unit and / or the artificial intelligence unit to process the data to implement the digital twin service.

[0017] In some embodiments, the data circulation technology includes blockchain technology and data privacy computing technology.

[0018] In some embodiments, the processing device is further configured to map at least a portion of the data to a virtual hospital using at least a portion of the extended reality unit, the artificial intelligence unit, and the digital twin unit; the user space application is configured to allow the relevant users to interact with the virtual hospital so that the relevant users can obtain at least a portion of the user services.

[0019] In some embodiments, the processing device is further configured to: when the relevant user interacts with the virtual hospital, present at least a portion of the virtual hospital to the relevant user by using the extended reality technology through the extended reality unit.

[0020] In some embodiments, data interaction in the hospital support platform satisfies preset data privacy rules and data security rules.

[0021] In some embodiments, the artificial intelligence unit includes an agent unit, which is configured to maintain an agent that realizes autonomous learning and evolution based on AI technology and data related to the hospital business.

[0022] In some embodiments, the intelligent agent includes a pre-consultation intelligent agent corresponding to the pre-consultation service, and the pre-consultation intelligent agent is configured to: conduct a pre-consultation inquiry to the patient through the patient terminal based on the department where the doctor with whom the patient is registered is located; and generate the pre-consultation record based on the data collected by the patient terminal in the pre-consultation inquiry.

[0023] In some embodiments, the pre-consultation agent is further configured to determine the content of the pre-consultation inquiry based on the department where the doctor with whom the patient is registered is located, including: obtaining the pre-consultation record template corresponding to the department where the doctor is located and the known information of the patient; determining the missing information that has not been collected in the pre-consultation record template by comparing the pre-consultation record template with the known information of the patient; and determining the inquiry content based on the missing information.

[0024] In some embodiments, the pre-consultation agent is further configured to determine the content of the pre-consultation inquiry based on the department of the doctor with whom the patient is registered, including: using a missing information determination model to process the department where the doctor is located and known information about the patient to determine the missing information to be collected from the patient; 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.

[0025] In some embodiments, the pre-consultation inquiry is conducted based on inquiry content and includes multiple rounds of inquiry, and the inquiry content includes the inquiry content of each round of inquiry, and the initiating the pre-consultation inquiry to the patient includes: for each round of pre-consultation inquiry except the first round of inquiry, based on the data collected before the current round of inquiry, determining the semantic information and emotional information of the patient's historical answers; based on the semantic information and the emotional information, adjusting the inquiry content of the current round of inquiry; and based on the adjusted inquiry content of the current round of inquiry, conducting the current round of inquiry through the patient terminal.

[0026] In some embodiments, the pre-consultation includes multiple rounds of inquiries, and the pre-consultation inquiries to the patient include: for each current round of inquiries except the first round of inquiries, based on the inquiry content of historical inquiries, the patient's historical answers and the patient's known information, using the inquiry content determination model 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 inquiry content corresponding to the current round of inquiries, the current round of inquiries is conducted through the patient terminal.

[0027] In some embodiments, the intelligent agent includes a consultation intelligent agent corresponding to the consultation service, and the consultation intelligent agent is configured to: during the patient's consultation process, determine whether the patient needs to communicate with the remote accompanying person based on the perception information collected by the perception device during the consultation process; in response to determining that the patient needs to communicate with the remote accompanying person, control at least one terminal device to enlarge the interface elements related to the remote accompanying service.

[0028] In some embodiments, the intelligent agent includes an inpatient intelligent agent corresponding to the inpatient service, and the inpatient intelligent agent is configured to: determine whether the patient meets the conditions for admission examination in the ward based on the perception information collected by the perception equipment in the ward; in response to determining that the patient meets the conditions for admission examination, control the intelligent nursing cart to guide the nurse into the ward, and control the intelligent nursing cart to present information related to the admission examination; generate an admission record based on the physical examination data of the patient collected during the admission examination.

[0029] In some embodiments, the intelligent agent includes an inpatient intelligent agent corresponding to the inpatient service, and the inpatient intelligent agent is configured to: for each day of the patient's hospitalization, determine the patient's daily plan based on the patient's patient data and the doctor's medical orders to the patient, the daily plan including at least one medical operation that needs to be performed on the patient on that day; display the daily plan to the patient through a terminal device in the patient's ward; and display the daily plan to the nurse corresponding to the patient through the terminal device of the nurse.

[0030] In some embodiments, the intelligent agent includes a surgical intelligent agent corresponding to the surgical service, and the surgical intelligent agent is configured to: determine a planned route from the patient's current location to the waiting area of ​​the operating room; control an intelligent wheelchair to transport the patient to the waiting area along the planned route; provide preoperative education to the patient through the patient's patient terminal based on the patient's patient data and surgical plan during the patient's transportation to the waiting area; and after the patient is transported to the waiting area, verify the patient's identity based on the patient's biometric information collected by the sensing device in the waiting area. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0032] Figure 1 is a block diagram of an exemplary medical service system according to some embodiments of the present specification;

[0033] Figure 2 is a schematic diagram of an exemplary medical service system according to some embodiments of the present specification;

[0034] Figure 3 is a schematic diagram of the architecture of a hospital support platform according to some embodiments of this specification;

[0035] Figure 4 is an exemplary flow chart of a process of verifying a hardware device according to some embodiments of this specification;

[0036] Figure 5 is an exemplary schematic diagram of a data lake warehouse according to some embodiments of this specification;

[0037] Figure 6 is an exemplary schematic diagram of a data processing method according to some embodiments of this specification;

[0038] Figure 7 is an exemplary schematic diagram of a method for storing data according to some embodiments of this specification;

[0039] Figure 8 is an exemplary schematic diagram of an application development layer according to some embodiments of this specification;

[0040] Fig. 9A is a schematic diagram of an exemplary process for providing pre-consultation services according to some embodiments of this specification;

[0041] Fig. 9B is a schematic diagram of an exemplary process of performing a second inquiry according to some embodiments of this specification;

[0042] Fig.10 is a schematic diagram of an exemplary process of providing medical outpatient services based on perception information according to some embodiments of this specification;

[0043] Fig.11 It is a schematic diagram of an exemplary process of providing services to users related to the hospital admission process according to some embodiments of this specification;

[0044] Fig.12 is a schematic diagram of an exemplary process for providing nursing services according to some embodiments of this specification;

[0045] Fig.13 is a schematic diagram of a preoperative guidance process according to some embodiments of this specification; and

[0046] Fig.14 is a schematic diagram of an exemplary process for performing a surgery according to some embodiments of the present specification. DETAILED DESCRIPTION

[0047] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0048] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0049] Unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0050] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0051] Some embodiments of the present specification provide a hospital support platform, including a hardware layer (also called a hardware device module), an interface layer (also called an interface module), a data processing layer (also called a data processing module), an application development layer (also called an application development module), and a service layer (also called a meta-service layer, a meta-service module, a service module). The hardware layer is configured to collect data related to hospital business; the interface layer is configured to obtain data from the hardware layer and send the data to the data processing layer; the data processing layer includes a plurality of data processing units, which are configured to obtain data sent by the interface layer and use at least one of the plurality of data processing units to process the data to implement user services related to hospital business; the application development layer is configured to provide an open interface for developers to call at least a part of the data processing units and use at least a part of the data processing units for application development; the service layer is configured to provide user space applications for users related to hospital business to obtain user services related to hospital business.

[0052] In some embodiments, the hospital support platform includes hardware devices (as a hardware layer), software and hardware interfaces (as an interface layer), a data center and processing devices (as a data processing layer), an open interface (as an application development layer), and a user space application (as a service layer). The hardware device is configured to collect data related to the hospital's business. The software and hardware interface is configured to obtain data from the hardware device and send the data to the data center for storage. The data center includes a data lake, which is configured to store data persistently in a tamper-proof manner. The processing device is configured with data processing units, such as an extended reality unit, an artificial intelligence unit, a digital twin unit, and a data circulation unit. The processing device can use at least one of the above-mentioned data processing units to process at least a portion of the data stored in the data center, thereby realizing user services. The open interface is configured for application developers to call at least a portion of the data processing units and use at least a portion of the data processing units for application development. For more descriptions of hardware devices, data centers, processing devices, user space applications, open interfaces, and software and hardware interfaces, see Figure 3 .

[0053] Some embodiments of this specification provide a hospital support platform, which is configured to comprehensively manage various types of hospital resources, including hardware resources, software resources, data resources, etc. In some embodiments, the hospital support platform integrates multiple data processing units that support various advanced technologies, including artificial intelligence (AI) technology, extended reality (XR) technology, digital twin technology, and blockchain technology, etc. These advanced technologies are used to improve the service efficiency and quality of the medical industry. For example, artificial intelligence technology can realize the autonomous evolution and continuous optimization of hospital operations, and XR technology and digital twin technology can realize the creation and maintenance of virtual hospitals. Virtual hospitals can interact with users and provide users with an immersive and novel virtual-real fusion service experience. In addition, the hospital support platform also includes an application development layer, which enables third-party developers in the medical industry to access these advanced technologies, thereby building an open medical ecosystem, promoting application development and innovation, and promoting the development of the medical industry.

[0054] Figure 1 is a block diagram of an exemplary medical service system according to some embodiments of the present application.

[0055] The medical service system 100 can also be called a meta-hospital system. It is built based on a variety of innovative technologies, including metaverse technology, XR technology (for example, augmented reality (AR) technology, virtual reality (VR) technology, mixed reality (MR) technology, etc.), AI technology, digital twin technology, IOT technology, data circulation technology (for example, blockchain technology, data privacy computing technology), spatial computing technology, image rendering technology, etc.

[0056] 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 related users of the physical hospital 110 through the user space application 120.

[0057] Physical hospital 110 refers to a hospital that exists in the physical world and has tangible attributes.Herein, healthcare facilities that provide medical, surgical, and psychiatric care and treatment to people are collectively referred to as hospitals.

[0058] like Figure 1 As shown, the physical hospital 110 may include multiple physical entities. For example, the multiple physical entities may include departments, users, hardware equipment, user services, public areas, medical service processes, etc., or any combination thereof.

[0059] Departments are specialized units or departments that provide specific types of medical care, treatment, and services. Each department may focus on a particular area of ​​medicine and may be staffed by health care professionals with expertise in that area. For example, departments may include outpatient departments, inpatient departments, surgical departments, support departments (e.g., registration departments, pharmacy departments), internal medicine, surgery, specialty medicine, child health departments, etc., or any combination thereof.

[0060] The user may include any user associated with the physical hospital 110 (or referred to as a related user of the physical hospital 110). For example, the user may include a patient (or a part of a patient (e.g., an organ)), a companion, a visitor of a patient, a hospital staff of the physical hospital 110, a supplier of the physical hospital 110, an application developer of the physical hospital 110, etc., or any combination thereof. The hospital staff of the physical hospital 110 may include medical service providers (e.g., doctors, nurses, technicians, etc.), hospital administrators, support staff, or the like, or any combination thereof. Exemplary hospital administrators may include department nursing administrators, clinical administrators, department directors, hospital directors, hospital administrators, functional administrators, or the like, or any combination thereof.

[0061] The hardware devices may include hardware devices located in the physical hospital 110 and / or hardware devices that communicate with hardware devices in the physical hospital 110. Exemplary hardware devices may include terminal devices, medical service devices, sensing devices, basic devices, etc., or any combination thereof.

[0062] The terminal device may include a terminal device that interacts with a user of the medical service system 100. For example, the terminal device may include a terminal device that interacts with a patient (also referred to as a patient terminal), a terminal device that interacts with a patient's doctor (also referred to as a doctor terminal), a terminal device that interacts with a nurse (also referred to as a nurse terminal), a terminal device that interacts with a remote visitor (also referred to as a remote terminal device), or a public terminal of a hospital (e.g., a consulting room terminal, a bedside terminal device, a terminal device in a waiting area, an intelligent surgical terminal), etc., or any combination thereof. In the present application, unless clearly obtained from the context or otherwise specified in the context, terminal devices owned by a user and terminal devices provided to a user by the physical hospital 110 are collectively referred to as terminal devices of the user or terminal devices that interact with the user.

[0063] The terminal device may include a mobile terminal, an XR device, a smart wearable device, etc. The mobile terminal may include a smart phone, a personal digital assistant (PDA), a display, a gaming device, a navigation device, a handheld terminal (POS), a tablet computer, etc., or any combination thereof.

[0064] 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 helmets, XR glasses, XR patches, stereo headphones, etc., or any combination thereof. For example, XR devices may include Google Glass TM 、Oculus Rift TM 、GearVR TM 、AppleVisionpro TM Etc. Specifically, the XR device may include a display component on which virtual content can be presented and / or displayed. In some embodiments, the XR device may further include an input component. The input component can enable interaction between a user and virtual content (e.g., a virtual surgical environment) displayed by the display component. For example, the input component may include a touch sensor, a microphone, an image sensor, etc., which is 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 component. The input component may include a handle, a glove, a stylus, a console, etc.

[0065] Smart wearable devices may include smart bracelets, smart shoes and socks, smart glasses, smart helmets, smart watches, smart clothes, smart backpacks, smart accessories, etc., or any combination thereof. In some embodiments, smart wearable devices may obtain physiological data (e.g., heart rate, blood pressure, body temperature, etc.) of the user.

[0066] The medical service equipment can be configured to provide medical services to patients. For example, the medical service equipment can include examination equipment, nursing equipment, treatment equipment, etc., or any combination thereof.

[0067] The inspection equipment may be configured to provide inspection services to the patient, for example, to collect the patient's inspection data. Exemplary inspection data may include heart rate, respiratory rate, body temperature, blood pressure, medical imaging data, body fluid test reports (e.g., blood test reports), etc., or any combination thereof. Accordingly, the inspection equipment may include a vital sign monitor (e.g., a blood pressure monitor, a blood glucose meter, a heart rate meter, a thermometer, a digital stethoscope, etc.), a medical imaging device (e.g., a computer tomography (CT) device, a digital subtraction angiography (DSA) device, a magnetic resonance (MR) device, etc.), a laboratory device (e.g., a routine blood test device, etc.), etc., or any combination thereof.

[0068] Nursing equipment can be configured to provide nursing services to patients and / or assist medical service providers in providing nursing services. Exemplary nursing equipment can include hospital beds, patient care robots, smart nursing carts, smart medicine boxes, smart wheelchairs, etc.

[0069] The therapeutic device can be configured to provide therapeutic services to patients and / or assist medical service providers in providing therapeutic services. Exemplary therapeutic devices can include surgical devices, radiotherapy devices, physical therapy devices, etc., or any combination thereof.

[0070] The perception device may be configured to collect perception information related to the environment in which it is located. For example, the perception device may include an image sensor, a sound sensor, etc. The image sensor may be configured to collect image data in the physical hospital 110, and the sound sensor may be configured to collect voice signals in the physical hospital 110. In some embodiments, the perception device may be an independent device or may be integrated into another device. For example, the sound sensor may be part of a medical service device or a terminal device.

[0071] The infrastructure can be configured to support data transmission, storage and processing. For example, the infrastructure can include networks, computer room facilities, computing equipment, computing chips, storage devices, etc.

[0072] In some embodiments, at least a portion of the hardware devices of the physical hospital 110 are IoT devices. IoT devices refer to devices with sensors, processing capabilities, software, and other technologies that connect and exchange 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.

[0073] User services may include any services provided to users by the hospital support platform 140. For example, user services include medical services provided to patients and / or accompanying persons, support services provided to staff of the physical hospital 110 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 in the following description.

[0074] Public areas refer to shared spaces accessible to users (or portions of users) in the physical hospital 110. For example, public areas may include reception areas (e.g., front desks), waiting areas, corridors and hallways, etc., or any combination thereof.

[0075] The medical service process refers to the process of providing corresponding medical services to patients. The medical service process usually includes several links and / or steps, and the user needs to go through these links and / or steps to obtain the corresponding medical services. Exemplary medical service processes may include outpatient processes, inpatient processes, surgical processes, or similar processes, or any combination thereof. In some embodiments, the 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 and the standard links involved in the medical service process and how to collect data related to the medical service process can be specified.

[0076] The user space application 120 provides users with access to user services provided by the hospital support platform 140. The user space application 120 can be an application, a plug-in, a website, a small program, or any other suitable form. For example, the user space application 120 is an application installed on a user terminal device, and the application includes a user interface for the user to initiate a request and receive the corresponding service.

[0077] 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 includes a patient space application corresponding to the patient, a medical space application corresponding to the doctor, a management space application corresponding to the manager, etc., or any combination thereof. The user services provided by the patient space application, the medical space application, and the 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, path guidance services, pre-consultation services, remote medical services, hospitalization services, discharge services, etc. Exemplary medical space services include scheduling services, surgical planning services, surgical simulation services, patient management services, remote ward rounds services, remote outpatient services, etc. Exemplary manager space services include monitoring services, medical service evaluation services, equipment parameter setting services, service parameter setting services, resource scheduling services, etc.

[0078] In some embodiments, the patient space application, the medical space application, and the management space application may be integrated into one user space application 120, and the user space application 120 may be configured to provide access portals for each type of user (e.g., patients, medical service providers, managers, etc.). As an example only, a specific user may have a corresponding account that can be used to log in to the user space application, view corresponding diagnosis and treatment data, and obtain corresponding user services.

[0079] According to some embodiments of the present specification, 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 his / her corresponding user space application. In addition, currently users usually 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 the present application can improve user experience, improve service quality and efficiency, enhance service security, and reduce development or operation costs.

[0080] In some embodiments, the user space application 120 can be configured to provide relevant users of the physical hospital 110 with an access portal for interacting with the virtual hospital 130. For example, through the user space application 120, the user can enter instructions for retrieving the digital content of the virtual hospital 130 (e.g., hardware equipment, patient organs, digital twin models of public areas), view the digital content, and interact with the digital content. As another example, through the user space application 120, the user can communicate with a virtual character representing an intelligent body. In some embodiments, the public terminal of the hospital can install a tube space application, and the administrator account of the department corresponding to the public terminal can be logged in in the tube space application. Users can receive user services through the tube space application installed in the public terminal.

[0081] The virtual hospital 130 is a digital twin (ie, a virtual representation or virtual copy) of the physical hospital 110 and is used to simulate, analyze, predict, and optimize the operating status of the physical hospital 110. For example, the virtual hospital 130 may be a real-time digital copy of the physical hospital 110.

[0082] In some embodiments, the virtual hospital 130 may be presented to the user using digital technology. For example, when the relevant user interacts with the virtual hospital 130, at least a portion of the virtual hospital 130 may be presented to the relevant user using XR technology. As an example only, at least a portion of the virtual hospital 130 may be superimposed on the relevant user's real-world view using MR technology.

[0083] In some embodiments, the virtual hospital 130 may include a digital twin of a physical entity associated with the physical hospital 110. A digital twin refers to a virtual representation of a physical entity (e.g., a virtual copy, a mapping, a digital simulator). A digital twin can reflect and predict the state, behavior, and performance of a physical entity in real time. For example, the virtual hospital 130 may include a digital twin of at least a portion of the medical services, departments, users, hardware equipment, user services, public areas, medical service processes, etc. of the physical hospital 110. The digital twin of a physical entity may be in a variety of forms, including models, images, graphics, text, numerical values, and the like. 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), virtual equipment (e.g., virtual imaging equipment and virtual scalpels) corresponding to medical service equipment (e.g., imaging equipment and scalpels), and the like.

[0084] In some embodiments, the 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 the update of the state of the corresponding physical entity. For example, in the process of mapping data related to the physical hospital 110 to the virtual hospital 130, one or more first digital twins may be updated. One or more second digital twins may be updated by at least one of the user space applications 120, and the update of each second digital twin may result in an update of the state of the corresponding physical entity. In other words, when the corresponding physical entity changes its state, the first digital twin may be updated accordingly; when the second digital twin is updated, the state of the corresponding physical entity also changes accordingly. 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 the digital twin may be a first digital twin or a second digital twin.

[0085] According to some embodiments of this specification, by generating a virtual hospital 130 that includes a digital twin of physical entities related to the physical hospital 110, the physical hospital 110 (including hardware equipment, users, user services, medical service processes, etc.) can be simulated and tested in a safe and controllable environment. Through virtual reality linkage (for example, 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. In addition, the use 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 improving the user experience.

[0086] In some embodiments, the virtual hospital 130 may further include an intelligent agent that achieves self-evolution based on data related to the physical hospital 110 and AI technology.

[0087] An agent refers to an agent that acts in an intelligent manner. For example, an agent may 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., medical service processes). Through AI technology (e.g., reinforcement learning, deep learning, etc.), the agent can continuously learn and self-optimize in interaction with the environment. In addition, the agent can collect and analyze massive data (e.g., relevant data of the physical hospital 110) through big data technology, and mine patterns and learning rules from the data to optimize the decision-making process, thereby identifying environmental changes in uncertain or dynamic environments, responding quickly, and making reasonable judgments. For example, the agent can autonomously learn and evolve based on AI technology to adapt to changes in the physical hospital 110. As an example only, the agent can be built based on NLP technology (e.g., large language models, etc.), and can automatically learn and autonomously update through a large amount of language text (e.g., hospital business data and patient feedback information) to improve the quality of user services provided by the physical hospital 110.

[0088] In some embodiments, agents may include different types of agents corresponding to different medical service processes, different user services, different departments, different diseases, different hospital positions (e.g., nurses, doctors, technicians, etc.), different links in the medical service process, etc. Agents of a specific type are used to process tasks corresponding to a specific type. In some embodiments, an 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, agents may operate with reference to basic configuration data (e.g., dictionaries, knowledge graphs, templates, etc.) of the departments and / or diseases corresponding to the agents. In some embodiments, multiple agents may collaborate and share information through network communications to jointly complete complex tasks.

[0089] In some embodiments, the configuration of the agent can be set. For example, basic configuration data used by the agent in operation can be set. The basic configuration data can include dictionaries, knowledge databases, templates, etc. For another example, the use rights of the agent can be set for different users. In some embodiments, the administrator of the physical hospital 110 can set the configuration of the agent through the management space application.

[0090] In some embodiments, the agent can be integrated into or deployed on a hardware device. For example, the agent corresponding to the inpatient service can be integrated into a hospital bed or a presentation device of a hospital bed. In some embodiments, the agent can be integrated into or deployed on an embodied intelligent robot. An embodied intelligent robot refers to a robotic system that combines physical presence (embodiment) with intelligent behavior (cognition). An embodied intelligent robot can be configured to interact with the real world in a way that mimics or supplements human capabilities, using physical form and cognitive functions to perform tasks, make decisions, and adapt to the environment. By leveraging artificial intelligence and sensor technology, embodied intelligent robots can operate autonomously, interact with the environment, and continuously improve performance. For example, an embodied intelligent robot can be configured with an agent corresponding to a surgical service and assist doctors in performing surgery.

[0091] In some embodiments, at least a portion of user services may be provided based on an agent. For example, at least a portion of user services may be provided to relevant users based on a processing result, wherein the processing result is generated by at least one of the agents 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 a medical service process of the physical hospital 110, the agent may include an agent corresponding to the medical service process, and user services may be provided to relevant users of the medical service process by processing the data using the agent corresponding to the medical service process.

[0092] The hospital support platform 140 may be configured to provide technical support to the medical 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 circulation 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 calculation.

[0093] In some embodiments, the hospital support platform 140 can support the interaction between the physical hospital 110 and the virtual hospital 130. For example, the processing device of the hospital support platform 140 can obtain data related to the physical hospital 110 from the hardware device and map the data related to the physical hospital 110 to the virtual hospital 130. For example, the processing device of the hospital support platform 140 can update a part of the digital twin in the virtual hospital 130 (e.g., one or more first digital twins) based on the obtained data, so that each part of the digital twin in the virtual hospital 130 can reflect the updated state 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 state of the physical entity related to the physical hospital 110 in real time, thereby realizing the monitoring and evaluation of the physical entity. As another example, the intelligent 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.

[0094] In some embodiments, the hospital support platform 140 may 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, a processing device of the hospital support platform 140 may provide a user service corresponding to the service request. For another example, in response to detecting that a user service needs to be provided to a user, the processing device of the hospital support platform 140 may control a physical entity or a virtual entity corresponding to the user service to provide the user service. For example, in response to detecting that a patient is admitted to a hospital ward, the processing device of the hospital support platform 140 may control a smart nursing cart to guide a nurse to the hospital ward to perform an admission examination on the patient.

[0095] In some embodiments, at least a portion of 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., conversation, 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 the digital twin in the virtual hospital 130, the interaction between the relevant user and the intelligent agent, the interaction between the relevant user and the virtual character, etc., or any combination thereof.

[0096] In some embodiments, at least a portion of user services may 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 a second digital twin input by a relevant user may be received through the user space application 120, and the corresponding physical entity of the second digital twin may be updated according to the update instruction. As another example, a user may view a first digital twin of a physical entity (e.g., a 3D digital twin model of a patient's organ or a hardware device) through the user space application 120 to understand the state of the physical entity. Optionally, the user may change the display angle, display size, etc. of the digital twin.

[0097] 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 the relevant user, and provide at least part of the user service to the relevant user based on the interaction between the relevant user and the virtual character.

[0098] 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. Figure 3 In some embodiments, the hardware devices of the physical hospital 110 may be part of the hospital support platform 140 .

[0099] According to some embodiments of the present specification, 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, etc.). The virtual hospital can reflect the real-time status (e.g., changes, updates, etc.) of the physical entities related to the physical hospital, thereby enabling monitoring and evaluation of the physical entities. This integration can provide accurate data support for the operation and intelligent decision-making of medical services. In addition, through the virtual hospital, users related to medical services can jointly establish an open and shared ecosystem, thereby promoting the innovation and improvement of medical services.

[0100] In addition, it is possible to provide full-life cycle healthcare services for patients that are linked inside and outside the hospital. The perspective of medical services has expanded from simple disease treatment to cover the entire life cycle of patients, including prevention, diagnosis, treatment, rehabilitation, health management, etc. By establishing linkages inside and outside the hospital, physical hospitals can better integrate online and offline resources to provide patients with comprehensive and continuous medical and health services. For example, through remote monitoring and online medical consultations, patients' health conditions can be followed up in real time, treatment plans can be adjusted in a timely manner, and treatment effects can be improved.

[0101] Figure 2 is a schematic diagram of an exemplary medical service system according to some embodiments of the present application.

[0102] like Figure 2 As shown, the medical service system 200 may include a processing device 210, a network 220, a storage device 230, one or more medical service devices 240, one or more sensing devices 250, one or more patient terminals 260 of a patient 261, and one or more doctor terminals 270 of a doctor 271 associated with the patient 261. In some embodiments, the components in the medical service system 200 may be interconnected and / or communicated via wireless connections, wired connections, or a combination thereof. The connections between the components of the medical service system 200 may be variable.

[0103] The processing device 210 may process data and / or information obtained from the storage device 230, the medical service device 240, the sensing device 250, the patient terminal 260, and / or the doctor terminal 270. For example, the processing device 210 may map data related to a physical hospital to a virtual hospital corresponding to the physical hospital, and provide user services to the patient 261 and the doctor 271 through the patient terminal 260 and / or the doctor terminal 270, respectively, by processing the data related to the physical hospital. As another example, the processing device 210 may maintain a digital smart object, and provide user services to the patient 261 and the doctor 271 through the patient terminal 260 and / or the doctor terminal 270, respectively, by allowing the digital smart object to participate in processing the data related to the physical hospital.

[0104] In some embodiments, the processing device 210 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, the processing device 210 may be located locally or remotely from the medical service system 200. In some embodiments, the processing device 210 may be implemented on a cloud platform. For example, a cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud cloud, a multi-cloud, etc., or any combination thereof.

[0105] In some embodiments, the processing device 210 may include one or more processors (e.g., a single-core processor or a multi-core processor). For illustration 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 in the present application may also include multiple processing devices. Therefore, as in the present application, the operations and / or method steps performed by one processing device 210 may also be performed jointly or individually by multiple processing devices.

[0106] The network 220 may include any suitable network capable of facilitating information and / or data exchange of the healthcare service system 200. The network 220 may be or include a wired network, a wireless network (e.g., an 802.11 network, a Wi-Fi network), a Bluetooth TM network, near field communication (NFC) network, etc., or any combination thereof.

[0107] The storage device 230 may store data, instructions, and / or any other information. In some embodiments, the storage device 230 may store data obtained from other components of the healthcare delivery system 200. In some embodiments, the storage device 230 may store data and / or instructions that the processing device 210 may execute or use to execute the exemplary methods described in this application.

[0108] In some embodiments, the data stored in the storage device 230 may include multimodal data. Multimodal data may include data in multiple forms (e.g., images, graphics, videos, text, etc.), various types of data, data obtained from different sources, data related to different medical services (e.g., diagnosis, surgery, rehabilitation, etc.), and data related to different users (e.g., patients, medical staff, managers, etc.). For example, the data stored in the storage device 230 may include medical data reflecting the health status of the patient 261. For example, the medical data may include an electronic health record of the patient 261. An electronic health record refers to an electronic file that records various types of patient data (e.g., basic information, examination data, imaging data). For example, an electronic health record may include a three-dimensional model of multiple organs and / or tissues of the patient 261.

[0109] In some embodiments, the storage device 230 may include a mass storage device, a removable storage device, a volatile read-write memory, a read-only memory (ROM), etc., or any combination thereof. In some embodiments, the storage device 230 may include a data lake and a data warehouse. Figure 3 Describe in detail.

[0110] The medical service device 240 can be used to provide or assist medical services. Figure 2 As shown, the medical service equipment 240 includes a clinic terminal 240-1, a hospital bed 240-2, an intelligent surgery terminal 240-3, an intelligent nursing cart 240-4, an intelligent wheelchair 240-5, etc., or any combination thereof.

[0111] The clinic terminal 240-1 refers to a terminal device configured in the clinic for use by doctors and patients in the medical outpatient process. For example, the 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 the clinic terminal 240-1 may display a consultation interface, and data may be displayed on the consultation interface to facilitate communication between doctors and patients. Exemplary data may include electronic health records (or part thereof), pre-consultation records, medical images, 3D organ models, test results, consultation recommendations, etc.

[0112] The hospital bed 240-2 refers to a bed in a hospital ward that can support inpatients and provide user services to patients. The hospital bed 240-2 may include a bed, a bedside terminal device, a bedside inspection device, a sensor, etc., or any combination thereof. The bedside terminal device may include an XR device, a display device, a mobile device, etc., or any combination thereof. In some embodiments, the hospital bed 240-2 may be controlled by an intelligent agent corresponding to an inpatient service, wherein the hospital bed may also be referred to as an intelligent hospital bed or a meta-hospital bed.

[0113] The intelligent surgical terminal 240-3 refers to a device configured with an intelligent agent for assisting surgery, and is controlled by an intelligent agent corresponding to the surgical service. The intelligent surgical terminal 240-3 can perceive the interaction (e.g., conversation, behavior, etc.) between the medical service provider, the patient, and the intelligent agent, and obtain the 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 operations based on the intelligent agent configured therein, generate surgical records of the surgical process, etc.

[0114] The smart nursing cart 240-4 refers to a nursing cart with an automatic driving function that can assist in the treatment and care of patients. For example, the smart nursing cart 240-4 can be configured to guide a nurse to a hospital ward for an admission examination of a patient. In some embodiments, the smart nursing cart can be controlled by an intelligent agent (e.g., an intelligent agent corresponding to an inpatient service, a nursing intelligent agent). In some embodiments, the smart nursing nursing cart 240-4 may include a trolley, a presentation device, one or more inspection devices and / or nursing tools, a sensing device (such as an image sensor, a GPS sensor, a sound sensor, etc.), etc. In some embodiments, the smart nursing cart 240-4 may be configured to obtain relevant treatment and nursing information of the patient, and generate physical examination data, nursing data, etc. The 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 operators, nursing measures, patient reactions, etc.

[0115] Smart wheelchair 240-5 refers to a transportation device for intelligently picking up and dropping off patients. In some embodiments, smart wheelchair 240-5 can be configured to perform autonomous navigation through integrated sensors and maps, locate the patient's position using radio frequency identification devices (RFID), Bluetooth or Wi-Fi signals, and identify the patient through biometric technology. In some embodiments, smart 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, smart wheelchair 240-5 can be configured to generate data (e.g., a record of the content of the interaction between the intelligent agent and the patient) by sensing interaction data through a built-in camera / sensor.

[0116] The sensing device 250 may be configured to collect sensing information related to the environment in which it is located. In some embodiments, the sensing device 250 may include a sensing device 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, and the like.

[0117] The patient terminal 260 may be a terminal device that interacts with the patient 261. In some embodiments, the patient terminal 260 may include a mobile terminal 260-1, an XR device 260-2, a smart wearable device 260-3, etc. The doctor terminal 270 may be a terminal device that interacts with the doctor 271. In some embodiments, the doctor terminal 270 may include a mobile terminal 270-1, an XR device 270-2, etc. In some embodiments, the patient 261 may access user space applications (e.g., patient space applications) through the patient terminal 260, and the doctor 271 may access user space applications (e.g., medical space applications) through the doctor terminal 270. In some embodiments, the patient 261 and the doctor 271 may communicate remotely with each other through the patient terminal 260 and the doctor terminal 270, thereby providing telemedicine services, such as remote outpatient services, remote ward rounds services, remote follow-up services, etc.

[0118] The sensing device 250, the patient terminal 260, and the doctor terminal 270 may be configured as data sources to provide information to the medical service system 200. For example, these devices may transmit the collected data to the processing device 210, and the processing device 210 may provide user services based on the received data.

[0119] It should be noted that the description of the above-mentioned medical service systems 100 and 200 is intended to be illustrative, not to limit the scope of the present 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 may be combined in various ways to obtain additional and / or optional exemplary embodiments. For example, the medical service system 200 may include one or more additional components, such as terminal devices of other users, public terminal devices of hospitals, etc. As another example, two or more components of the medical service system 200 may be integrated into a single component.

[0120] Figure 3 It is a schematic diagram of the architecture of the hospital support platform shown in some embodiments of this specification.

[0121] like Figure 3As shown, the hospital support platform 300 may include a hardware layer 310, an interface layer 320, a data processing layer 330, an application development layer 340, and a service layer 350. In this specification, unless clearly obtained from the context or otherwise specified in the context, the term "layer" and the term "module" may be used interchangeably. For example, the hardware layer may also be referred to as a hardware module, the interface layer may also be referred to as an interface module, the data processing layer may also be referred to as a data processing module, the application development layer may also be referred to as an application development module, and the service layer may also be referred to as a service module. It should be understood that the "layers" and "modules" in this specification are only used to logically divide the components in the hospital support platform, and are not intended to be limited thereto.

[0122] Hospital support platform can refer to a platform used to provide support for the operation and management of the hospital. For example, the hospital support platform can be used to support the scheduling, coordination, control and processing of resources (such as hardware resources, data resources, etc.); it can also be used to support the services provided to various users and institutions (such as medical services, artificial intelligence services, operation services, etc.).

[0123] The hardware layer 310 can provide a hardware foundation for the interaction between the real world and the digital world, and may include one or more hardware devices related to hospital operation. Exemplary hardware devices include medical service devices, sensing devices, terminal devices, basic devices, etc.

[0124] Medical service equipment may include various types of equipment used in medical services (such as diagnosis, treatment, rehabilitation, etc.). For example, it may include large medical devices such as medical scanning equipment (such as CT equipment, PET / CT equipment, MRI / CT equipment, ultrasound imaging equipment, etc.), surgical robots, etc. For another example, medical service equipment may include small portable or implantable medical health equipment or sensors such as bedside monitors, hearing aids, smart watches, and pacemakers.

[0125] The sensing device is used to sense the environment in which it is located and collect corresponding sensing information. Exemplary sensing devices include various sensors such as image sensors, sound sensors, temperature sensors, humidity sensors, etc. The sensing device can be an independent device, for example, a monitoring device installed in a consulting room. The sensing device can also be integrated into other devices, for example, a sound sensor can be integrated into a terminal device.

[0126] The terminal device can interact with users (such as patients, doctors, nurses, hospital managers, etc.). Exemplary terminal devices include mobile phones, tablet computers, laptops, wearable devices, displays, etc. In some embodiments, the terminal device may also include an extended reality (XR) device to allow users to experience and interact with an immersive digital environment. XR devices may include one or a combination of VR devices, AR devices, MR devices, etc.

[0127] Infrastructure is used to provide the hardware foundation for data transmission, storage and processing. Infrastructure may include networks, computer room facilities, computer equipment (such as processing equipment), computing chips, storage devices, etc.

[0128] In some embodiments, the hardware devices in the hardware layer 310 can be used to collect data related to hospital business. For example, medical scanning equipment can be used to collect medical imaging data; terminal equipment can be used to collect interaction data with users; and sensing equipment can be used to collect sensing information.

[0129] In some embodiments, one or more of the above hardware devices may be Internet of Things (IoT) devices. IoT devices refer to hardware devices that can sense, collect and transmit data through the Internet. For example, the medical service equipment and sensing devices described above may be IoT devices, which can send the collected data to other layers of the hospital support platform 300 for storage and / or processing through communication technologies (such as wired / wireless networks, Bluetooth, Zigbee, LoRaWAN, etc.).

[0130] In some embodiments, at least some of the hardware devices (such as each hardware device) in the hardware layer 310 need to comply with preset hardware standards. The preset hardware standards may include, but are not limited to, device specifications (device size, model), data transmission protocols (such as data transmission method, data structure, data type, etc.), device manufacturers, etc.

[0131] In some embodiments, the hardware layer 310 may include a hardware management device, which may be used to generate and update hardware configuration information of hardware devices. For more information about hardware configuration information, see Figure 4 and its description.

[0132] The interface layer 320 is connected to the hardware layer 310 and the data processing layer 330. The interface layer 320 can be used to obtain data collected by the hardware devices in the hardware layer 310 and send the data to the data processing layer for storage and / or processing. The interface layer 320 can also be used to control at least some of the hardware devices in the hardware layer 310.

[0133] In some embodiments, the interface layer 320 may include a hardware interface and a software interface (also referred to as a hardware-software interface).

[0134] The hardware interface may be used to achieve physical connection or communication connection with the hardware devices of the hardware layer 310. The hardware interface may include a wired communication interface, such as a serial communication interface, a parallel communication interface, a Universal Serial Bus (USB) interface, an Ethernet interface, etc. The hardware interface may include a wireless communication interface, such as a Wi-Fi interface, a Bluetooth interface, a Near Field Communication interface, etc.

[0135] Software interfaces define how different software components or systems interact with each other. Unlike hardware interfaces, which involve physical and electrical connections, software interfaces are abstract methods that support communication, data exchange, and function calls between software entities. Software interfaces can include Application programming interface (API), protocols such as Hyper Text Transfer Protocol (HTTP), File Transfer Protocol (FTP), Simple Object Access Protocol (SOAP), etc.

[0136] In some embodiments, the software interface may include a data interface for implementing data interaction with a hardware device. Different hardware devices may correspond to different data interfaces. For example, a medical imaging device may transmit the collected medical imaging data to the interface layer 320 via a medical data interface.

[0137] The interface layer 320 obtains or receives data collected by the hardware device through the data interface to provide a data basis for the data processing layer 330. It should be noted that the data interface will not make any modifications to the data content when transmitting data, thereby ensuring that the original data collected by the hardware device can be transmitted to the data processing layer 330 for storage and / or processing. In some embodiments, the data interface defines standard information for data transmission, which is used to indicate the protocol, format and mode of data transmission. The data transmission standard information may include standard data transmission protocols in the industry, such as the Digital Imaging and Communications in Medicine (DICOM) protocol, etc. The data transmission standard information may include a custom data transmission protocol, which can be set according to actual conditions (such as security requirements).

[0138] In some embodiments, the interface layer 320 may be configured to control at least a portion of the hardware device. Figure 3 As shown, the software interface may also include a control interface, which may be used to control at least a portion of the hardware device. For example, it may send a control instruction (such as a command, a code instruction) to the hardware device through the control interface, so that the hardware device executes the function or behavior corresponding to the control instruction and feeds back relevant information (such as status information).

[0139] In some embodiments, the control instruction may be generated by the data processing layer 330 (such as a data processing unit), that is, the data processing layer 330 may interact with the hardware layer 310 through the interface layer 320. The control instruction may be generated according to different hardware devices and their control protocols. For example, the control instruction may include but is not limited to a hardware device identifier, a control parameter (such as an operating parameter such as a rotation angle and a moving direction), and the like.

[0140] It should be noted that the data interface and / or the control interface can be implemented as software and can be stored in any type of non-transitory computer-readable medium or storage device. In some embodiments, the data interface and / or the control interface can be called by other units / modules (such as the data processing unit of the data processing layer 330) or hardware devices (such as the hardware devices of the hardware layer 310), and / or can be called in response to detected events.

[0141] In some embodiments, the interface layer 320 may also include a preset algorithm (not shown in the figure) decoupled from the medical service, which is used to perform processing that is unrelated to or weakly related to the medical service. As an example, the preset algorithm decoupled from the medical service may include a data flow analysis algorithm, a basic AI algorithm, and the like. For example, without affecting the data content, the data flow (such as data transmission frequency, data volume, etc.) is analyzed by a data flow analysis algorithm and / or a basic AI algorithm to monitor the data flow. For another example, the basic AI algorithm in the interface layer 320 can be called by the data processing unit in the data processing layer 330 to implement processing tasks related to hospital business.

[0142] In some embodiments, the interface layer 320 or a portion thereof may be integrated with the data processing layer 330. For example, the data interface and / or the control interface may be deployed in the data processing layer 330 as a part of the data processing layer 330. Exemplarily, the data interface and / or the control interface may be provided in the data processing layer 330 in the form of an interface unit or module.

[0143] The data processing layer 330 is used to store and / or process data. For example, the data processing layer 330 may include a data processing unit. The data processing layer 330 is configured to obtain data from the interface layer 320 and process the data through at least one of the data processing units to implement user services related to hospital business.

[0144] The data processing unit may include various preset algorithms for implementing data processing, which may be in the form of software, programs, computer codes and / or instructions implemented in various computer programming languages ​​(such as Java, C / C++). In some embodiments, the data processing layer 330 includes a processing device (such as Figure 2 The data processing unit may be configured on the processing device 220 as shown.

[0145] In some embodiments, the data processing unit may include an extended reality (XR) unit, which is configured to implement extended reality services using extended reality technology. Among them, extended reality services may include VR services, AR services, and MR services. For example, by providing MR services, digital content (such as three-dimensional organ models, virtual characters) in a virtual hospital can be superimposed on the user's real field of view, so that the user can interact with the digital content.

[0146] In some embodiments of this specification, by integrating an extended reality unit, the hospital support platform is able to support extended reality services, providing users (such as medical staff and patients) with a more intuitive and natural way of interaction in medical services, thereby improving user service efficiency and quality.

[0147] In some embodiments, the data processing unit may include an artificial intelligence (AI) unit configured to implement artificial intelligence services using artificial intelligence technologies, including but not limited to machine learning (ML), deep learning (DL), natural language processing (NLP), computer vision (CV), speech recognition and other technologies.

[0148] In some embodiments, the AI ​​unit may include multiple AI subunits, at least some of which may correspond to different hospital services and / or tasks, and are used to process data related to different hospital services and / or implement different tasks. Exemplarily, the AI ​​unit may include a natural language processing subunit, an image recognition subunit, a speech recognition subunit, etc.

[0149] In some embodiments, the artificial intelligence unit may include an agent unit built based on AI technology. Each agent unit is used to maintain an agent. An agent may refer to a software entity that can automatically perform tasks on behalf of a user and / or application, which can perceive the environment, process information, make decisions, and perform actions to achieve a specific purpose. The agent is designed to have characteristics such as adaptability, learning, autonomy, and goal-oriented behavior. In some embodiments, different agent units (i.e., different agents) can be set for different hospital business scenarios (such as diagnosis, surgery, etc.), roles (such as doctors, nurses, etc.), user services, etc., to provide corresponding agent services. For example, an agent unit may include a doctor agent unit, a nurse agent unit, a technician agent unit, etc.

[0150] In some embodiments, the agent can autonomously learn and evolve based on data related to hospital business collected by AI technology and hardware devices to adapt to changes in hospital business or the medical services it provides. As an example only, the agent can be built based on natural language processing technology (such as large prediction models, etc.), and automatically learn and autonomously update a large amount of language text (such as hospital business data, patient feedback information) to improve the quality of the services it provides.

[0151] In some embodiments of this specification, by integrating artificial intelligence units, the hospital support platform can have the ability to support artificial intelligence services, so as to realize efficient data analysis and processing in combination with artificial intelligence algorithms in medical services. In addition, by configuring intelligent agent units to maintain multiple intelligent agents, the processing of different hospital business scenarios or medical tasks is made more intelligent, and the hospital support platform can self-evolve to provide higher quality services.

[0152] In some embodiments, the data processing unit may include a digital twin unit configured to implement a digital twin service using digital twin technology.

[0153] Digital Twin technology can be used to digitize physical entities in the real world and realize the virtual-real linkage between the real world and the digital (virtualized) world. Among them, physical entities can be various real entities related to hospitals, such as physical space, personnel (such as doctors, nurses, etc.), hardware equipment, user services, medical processes, etc. Digital twins can be digital copies of physical entities, which can include but are not limited to 3D models, images, text and other representations. Exemplarily, digital twins can be virtual hospitals corresponding to hospital entities, virtual personnel (such as virtual doctors, virtual nurses, virtual patients) corresponding to personnel entities (such as doctors, nurses, patients), virtual equipment (such as virtual imaging equipment, virtual scalpels) corresponding to medical service equipment (such as imaging equipment, scalpels), etc.

[0154] Digital twin services can refer to the linkage or interactive services between physical entities in the real world and digital twins. For example, when the state of a physical entity in the real world changes, its corresponding digital twin can be updated accordingly. As an example only, the update of the state of medical service equipment, the update of the expression and posture of personnel, etc. will cause the update of its corresponding digital twin. Based on this type of digital twin that will be continuously updated with the corresponding physical entity, users can understand the real-time status of physical entities related to the hospital, thereby realizing the monitoring and evaluation of physical entities. For another example, when the digital twin of the virtual world is updated, its corresponding physical entity in the physical world can be updated accordingly. As an example only, hospital managers can update the parameters of digital twins corresponding to hardware equipment, medical services, medical processes, etc. through the management space application. Correspondingly, the parameters of hardware equipment, medical services, medical processes, etc. in the real world will also be updated accordingly. Based on this type of digital twin that can affect the state of the corresponding physical entity, users can realize the control and update of physical entities related to the hospital. For another example, a digital twin (such as a three-dimensional virtual patient model) can be presented to a user in the real world through XR technology, and the user can interact with the digital twin.

[0155] In some embodiments, the digital twin unit can process data based on the XR unit and / or the AI ​​unit to achieve high-quality digital twin services. For example, the digital twin unit can call the XR unit to use XR technology to present the digital twin to the user and enable the user to interact with the digital twin. For another example, the digital twin unit can call the AI ​​unit to use AI technology to achieve more accurate state mapping and state prediction.

[0156] In some embodiments of this specification, by setting up a digital twin unit, the hospital support platform is able to support digital twin services, and based on the digital twin services, realize real-time linkage and interaction between the real world and the virtual world, thereby improving the service quality of various user services.

[0157] In some embodiments, the data processing unit may include a data circulation unit configured to process data using data circulation technology to implement a data circulation service.

[0158] Data circulation services may include data transmission services, sharing services, exchange services, etc. For example, data circulation services may include data transmission and exchange services between different systems. In some embodiments, data circulation services may include data circulation services across medical institutions. For example, data circulation services may enable data sharing, transmission, and exchange between different medical institutions.

[0159] Data circulation technology may include various types of data privacy computing technology and / or data security technology. Data privacy computing technology can be used to process data according to various preset privacy protection rules to ensure that privacy information (such as user personal information) is not violated or leaked during data circulation. Among them, the preset privacy protection rules may be common rules or laws in the medical industry. Data privacy computing technology includes encryption technology, federated learning technology, privacy differential technology, multi-party secure computing technology, security outsourcing technology, etc. Data privacy computing can realize the separation of data ownership, management rights and usage rights and the circulation of data value.

[0160] Data security technology can be used to ensure the security, integrity and availability of data during circulation, and to prevent data from being accessed, leaked, tampered with or destroyed without authorization. Data security technology may include but is not limited to encryption technology, hash functions, digital signature technology, key exchange protocols, etc.

[0161] In specific applications, the data privacy computing technology and / or data security technology to be adopted can be determined based on actual circumstances or needs (such as the amount of data, the efficiency of data circulation, the degree of data privacy, the security level, etc.).

[0162] In some embodiments, the data circulation technology may include at least blockchain technology and data privacy computing technology. Blockchain technology is a decentralized distributed ledger technology that aims to securely record, verify and share information of multiple nodes in the network without the need for a central agency.

[0163] In some embodiments of this specification, by setting up a data circulation module, the hospital support platform has the ability to support data circulation across medical institutions and / or across systems. In addition, the introduction of blockchain technology and privacy computing technology can improve the security of data circulation and avoid data abuse or leakage.

[0164] In some embodiments, the data processing layer 330 also includes a data center to store data. The data center may include various storage devices / storage media, such as large-capacity storage devices, removable storage devices, volatile read-write memory, read-only memory (ROM), etc., or any combination thereof. Exemplarily, the data center may include large-capacity storage devices (such as disks, optical disks, solid-state drives), removable storage devices (optical disks, memory cards), random access memory (RAM), etc. In some embodiments, the data center may be deployed on a cloud platform (such as a public cloud, a private cloud).

[0165] In some embodiments, the data center adopts a lake-warehouse integrated architecture, which includes a data lake and a data warehouse (also called a data warehouse). The data lake is used to persistently store massive amounts of data. The data warehouse is used to store index data corresponding to the data in the data lake. The data stored in the data lake may include raw data collected by hardware devices, data generated based on the raw data, etc. The data stored in the data lake is multimodal, and may include data from different data sources (such as different hardware devices), data related to different medical services (such as diagnosis, surgery, rehabilitation, etc.), data related to different users (such as patients, medical staff, managers, etc.), and data of different data types (such as images, sounds, videos, files). In some embodiments, the data lake is configured to persistently store hospital business-related data collected by hardware devices in a tamper-proof manner. For more information about data lake warehouses, see Figure 5 and its description.

[0166] The application development layer 340 can be used to support application development, publishing, subscription, etc., and it can also be called an ecological suite layer.

[0167] In some embodiments, the application development layer 340 is configured to provide an open interface for application developers to access or call the data processing unit or a portion thereof, and use at least a portion of the data processing unit for application development. In other words, the various data processing capabilities of the data processing layer can be opened to application developers through the application development layer 340, so that application developers can develop various types of applications on this basis. Developers can include individuals, institutions (such as hospitals, IT technology companies) or any entity. An open interface can refer to an entrance that enables developers to access or call a data processing unit. In some embodiments, an open interface may include an application programming interface (Application Programming Interface, API) and the like.

[0168] In some embodiments, Figure 3 As shown, the application development layer 340 can provide development tools, application markets, multi-tenant operating platforms, cloud official websites, workspaces, and other support packages to assist developers in their work. For more information about development tools, application markets, and operating platforms, see Figure 8 and its description. The cloud official website is an open portal for developers to obtain various support services (such as development tools) provided by 340 of the application development layer. The workspace is used to combine and configure user workspaces and provide a work-oriented experience for doctors, patients and nurses.

[0169] In some embodiments of this specification, by setting up an application development layer, it is possible to provide multiple parties (such as individual developers, medical institutions, medical service equipment manufacturers, drug suppliers, IT technology companies, etc.) with access to various data processing units and various support kits, so as to promote the development of related applications and jointly promote the development of medical services and / or medical ecology.

[0170] The service layer 350 is used to enable relevant users to access and obtain user services related to hospital business through user space applications.

[0171] User services may include various services related to hospital business. Exemplary user services may include imaging services, electronic health record services, medical service equipment management services, extended reality services, disease screening services, visual computing services, doctor-patient communication services, etc. In some embodiments, user services may include patient space services for patients, medical space services for medical staff, and management space services for hospitals or medical institutions. In some embodiments, user services may be native services provided by the data processing layer 330, or they may be third-party services provided by the application development layer 340. For example, users can obtain user space applications published by third parties through the application market of the application development layer 340 to obtain third-party services.

[0172] User space applications are the entry point for users to obtain various user services, and are also the interactive interface for users to interact with the hospital support platform. User space applications include but are not limited to one or more combinations of application programs (such as Apps), websites (such as Websites), service interfaces (such as Service Interfaces), etc.

[0173] In some embodiments, Figure 3 As shown, user space applications may include patient space applications, medical space applications, and management space applications. Among them, patient space applications may refer to applications that provide patient space services for patients; medical space applications may refer to applications that provide medical space services for medical staff; and management space applications may refer to applications that provide management space services for managers of hospitals or medical institutions. Exemplary patient space applications include registration services, navigation services, pre-consultation services, remote consultation services, hospitalization services, discharge services, etc. Exemplary medical space services include scheduling services, surgical planning services, surgical simulation services, patient management services, remote ward rounds services, remote consultation services, etc. Exemplary management space services include regional monitoring services, medical service evaluation services, equipment parameter setting services, service parameter setting services, resource scheduling services, etc.

[0174] In some embodiments, the user space application may be provided or developed by the hospital. In some embodiments, the user space application may be provided or developed by a third party. For example, the third party may publish the user space application to the application market of the application development layer 340.

[0175] In some embodiments of this specification, by providing user space applications for each type of user, each type of user can easily obtain various services that he / she may use on his / her corresponding user space application. In the existing hospital service system, users are usually required to install various applications to obtain different services, resulting in poor user experience and high development costs. Compared with existing technologies, the solution in this specification can improve user experience, improve service quality, and reduce development costs.

[0176] In some embodiments, the data processing layer 330 may map at least a portion of the data to the virtual hospital using a data processing unit. Further, the user space application may include providing a portal for users to interact with the virtual hospital so that the users can obtain at least a portion of the user services in the service layer 350. In some embodiments, when the user interacts with the virtual hospital, the virtual hospital or a portion thereof may be presented to the user based on XR technology. In some embodiments, the virtual hospital or a portion thereof may be superimposed on the user's real world view using MR technology. For more information about virtual hospitals, see Figure 1 and its description.

[0177] It should be noted that the hospital support platform 300 is provided for illustrative purposes only and is not intended to limit the scope of this specification. For those of ordinary skill in the art, various modifications or changes can be made according to the description of this specification. However, these changes and modifications will not deviate from the scope of this specification. In some embodiments, one or more layers (such as the application development layer 340) can be omitted. In some embodiments, the hospital support platform 300 may also include one or more other layers. In some embodiments, two or more layers in the hospital support platform 300 may be merged into one layer, for example, the interface layer 320 may be integrated in the data processing layer 330. In some embodiments, a layer in the hospital support platform 300 may also be divided into multiple sub-layers, for example, the data processing layer 330 may be divided into a data storage sub-layer and a data processing sub-layer. In some embodiments, one or more layers of the hospital support platform 300 may be connected in sequence, for example, the hardware layer 310, the interface layer 320 and the data processing layer 330 may be connected in sequence and interact with each other in sequence. In some embodiments, the connection methods between different layers of the hospital support platform 300 may be diverse. For example, the service layer 350 may be directly connected to the data processing layer 330 (such as Figure 3 dashed line shown).

[0178] In some embodiments, the data interaction of the hospital support platform 300 (for example, the data interaction within each layer or between different layers in the hardware layer 310, the interface layer 320, the data processing layer 330, the application development layer 340 and the service layer 350) needs to comply with the preset data privacy specifications and data security rules. Specifically, any data acquisition party (including software and hardware) needs to undergo identity authentication and privacy verification when acquiring specific data. Identity authentication is used to verify whether the data acquisition party has the authority to acquire data. Privacy verification is used to verify whether the specific data contains privacy data (such as the patient's personal data) and whether the data acquisition party has the authority to access the privacy data. As an example only, the data processing unit of the data processing layer 330 and the API of the application development layer 340 need to undergo identity authentication and privacy verification when acquiring or accessing data in the data lake, and only after the verification is passed can the corresponding data be acquired or accessed. For another example, when the multi-tenants of the application development layer 340 access the data of other tenants, they need to undergo identity authentication first, and only when the tenant has access rights can they access the data of other tenants. In some embodiments, the preset data privacy specifications and data security rules may include data privacy specifications and data security specifications commonly used in the medical field, such as the Health Insurance Portability and Accountability Act (HIPPA) and the General Data Protection Regulation (GDPR).

[0179] Figure 4 is an exemplary flow chart of a process of verifying a hardware device according to some embodiments of this specification. In some embodiments, process 400 may be executed by interface layer 320. For example, the software and hardware interface included in interface layer 320 may be used to verify the hardware device connected thereto. Figure 4 As shown, process 400 includes the following steps.

[0180] Step 410: Obtain hardware configuration information of the hardware device.

[0181] The hardware configuration information may include basic information about the hardware, such as the name, model, manufacturer, and production date of the hardware device.

[0182] In some embodiments, the hardware configuration information may include device identity information, which is a unique identifier of the hardware. The device identity information may be generated according to a preset rule, for example, it may be determined based on the device's Mac address or a unique device ID or device number.

[0183] In some embodiments, the hardware configuration information may include operating status information of the hardware device, which may display the operating status of the hardware device (such as the current operating status). For example, the hardware configuration information may display whether the hardware device is abnormal, the type of abnormality, the number of abnormalities, the number of historical maintenance times, the service time, etc.

[0184] In some embodiments, the hardware configuration information of the hardware may be generated by the hardware device itself and sent to the interface layer 320. In some embodiments, the hardware layer 310 includes a hardware management device, which is configured to generate hardware configuration information of at least part of the hardware device and send the hardware configuration information to the interface layer 320. For example, the hardware management device may monitor the status of at least part of the hardware device (such as monitoring based on a heartbeat mechanism), and send the monitoring result to the interface layer 320 as the running status information.

[0185] Step 420, determining whether the hardware configuration information meets a preset condition.

[0186] The preset conditions may be used to evaluate whether the identity and / or operating status of the hardware device meets the expected requirements.

[0187] For example, for each hardware device in the hardware device (or a part thereof), the interface layer 320 may determine whether the hardware device is one of the multiple trusted devices based on the device identity information; in response to determining that the hardware device is one of the multiple trusted devices, the interface layer 320 may determine that the hardware configuration information corresponding to the hardware device meets the preset condition. In some embodiments, the multiple trusted devices may be preset by the hardware management device in the hardware layer 310. Exemplarily, the hardware management device may store a list of IDs of multiple trusted devices.

[0188] For another example, for each hardware device in the hardware device (or a part thereof), the interface layer 320 can determine whether the current operating status of the hardware device is normal based on the operating status information; in response to determining that the current operating status of the hardware device is normal, the interface layer 320 can determine that the hardware configuration information corresponding to the hardware device meets the preset conditions.

[0189] Step 430: In response to the hardware configuration information satisfying a preset condition, the data is transmitted to the data processing layer.

[0190] In some embodiments of the present specification, the interface layer 320 may first verify the identity and / or operating status of the hardware device, and only when the hardware passes the verification will the collected data be sent to the data processing layer. In this way, malicious or abnormal devices can be prevented from affecting the hospital support platform, and the reliability and accuracy of the data can be improved, thereby ensuring the accuracy of the user services provided subsequently.

[0191] Figure 5 This is an exemplary schematic diagram of a data lake warehouse according to some embodiments of this specification.

[0192] The data lake warehouse 520 includes a data lake 521 and a data warehouse 522. The data lake 521 can persistently store the data 510. Persistent storage is a way to save data within a preset time period, which can ensure that the stored data can still be accessed and maintain integrity even when the system is powered off or restarted.

[0193] Data 510 may include data of various types, structures, or formats. Figure 5 As shown, data 510 may include structured data 511, semi-structured data 512, and unstructured data 513. Structured data 511 is highly organized data, usually with a fixed data structure. Exemplary structured data 511 includes basic information of doctors, basic information of hardware equipment, archives, management / operation data, etc. Semi-structured data 512 has a certain structure, but this structure is not strict. Exemplary semi-structured data 512 includes clinical information / documents, wearable device health data, user behavior logs, device operation status logs, service metrics / logs / link information, etc. Unstructured data 513 has no predefined pattern or organization. Exemplary unstructured data 513 includes audio, video, images, scanned documents, three-dimensional models, machine learning models, digital twin models, ECG / pathology / cell / electron microscopy data, protein / genomics data, etc. In some embodiments, structured data 511 may be stored in a database (such as a relational database) in the form of a two-dimensional data table, and semi-structured data 512 or unstructured data 513 may be stored in the form of files or objects.

[0194] In some embodiments, data 510 may include raw data, which refers to data collected by a hardware device without any content modification. Raw data can be stored based on a native storage mode to avoid information loss caused by file format conversion. In some embodiments, data 510 may include derivative data generated based on raw data. For example, when data 510 is processed by a data processing unit, intermediate processing results and final processing results may be generated, and these processing results can be stored as derivative data in data lake 521.

[0195] In some embodiments, the data lake 521 may be configured to store the data 510 or a portion thereof in a tamper-proof form. For example, the original data stored in the data lake 521 may be set to a read-only mode to prevent it from being rewritten.

[0196] Due to the rapid development of the medical field, a certain type of raw data may be used in various medical services or tasks. Through the data lake 521, it can be ensured that the raw data collected by the hardware equipment is stored completely and securely for future use in various medical services or tasks.

[0197] The data warehouse 522 is used to store the data index corresponding to the data 510 to improve the retrieval efficiency of the data 510. Different types of indexes can be constructed for different types of data 510. For example, for structured data 511, a database index can be constructed; for semi-structured data 512 and / or unstructured data 513, a file index (such as a directory index, a full-text index, a metadata index, etc.) can be constructed. For the same data record, multiple data indexes can be constructed to achieve multi-dimensional data retrieval. For example, for CT images, data indexes such as patient ID, scanning device ID, and acquisition time can be constructed.

[0198] In some embodiments, the data lake warehouse 520 may also include a cache layer for storing temporary data or hot data. Temporary data may be derivative data of data 510. For example, it may be temporary data generated during medical business processing and has a shorter life cycle / storage cycle. Exemplarily, temporary data may be cleaned up after the medical business processing is completed. Hot data may be data that is accessed or read frequently, which may be related to one or more medical businesses and has a longer life cycle / storage cycle. For example, after a medical business is processed, it may continue to be stored in the cache area for access or reading when processing other medical businesses.

[0199] In some embodiments, Figure 5 As shown, the data lake warehouse 520 can provide data support for various medical business processing tasks to realize various user services 540. User services 540 may include report services (such as report generation and query), AI services, visualization / XR services, digital twin services, data transaction services and other user services. For more information about user services, see Figure 3 and its description.

[0200] In some embodiments, the data in the data lake 520 can be processed by a processing device 530. The processing device 530 may include one or more data processing units (such as XR units, digital twin units, etc.) in the data processing layer 330. For more information on how the data processing layer processes data, see Figure 6 and its description.

[0201] In some embodiments of the present specification, data is stored through a lake-warehouse integrated architecture, which can not only meet the needs of big data storage, but also provide reliable data support for complex medical business processing tasks, thereby providing users with more efficient user services.

[0202] Figure 6 It is an exemplary schematic diagram of a data processing method according to some embodiments of the present specification.

[0203] In some embodiments, the process 600 may be performed by a hospital support platform (such as the hospital support platform 300). The process 600 includes the following steps.

[0204] Step 610, obtaining data 601 from the hardware device.

[0205] like Figure 6 As shown, data 601 may include data obtained by the interface layer 320 from hardware devices (such as medical service devices, sensing devices, terminal devices, basic devices, etc.) of the hardware layer 310 through the data interface. For more information about the interface layer and the hardware layer, see Figure 3 and its description.

[0206] Step 620 , store the data 601 in the data lake 521 .

[0207] Data 601 can be persistently stored in the data lake 521 in a structured, semi-structured, or unstructured data format. For more information about the data lake 521, see Figure 5 and its description.

[0208] The following steps 630 to 661 may be executed by the data processing layer (such as the data processing unit therein).

[0209] Step 630: Process the data using the XR unit.

[0210] The XR unit can process the data 601 using the extended reality technology to realize the extended reality service. For example, based on the data 601, it can use one or a combination of VR, AR, and MR technologies to map the data 601 to a virtual hospital to realize the visualization display of the data 601 and human-computer interaction.

[0211] Step 640, use the AI ​​unit to process the data.

[0212] The AI ​​unit may use AI technology to analyze, predict, and process the data 601 to implement artificial intelligence services. For example, the AI ​​unit may use speech recognition technology to recognize the data 601 to obtain speech recognition results. In some embodiments, the AI ​​unit may interact with the user using an intelligent unit (such as a doctor intelligent unit, a nurse intelligent unit) based on the data input by the user, and generate corresponding feedback information.

[0213] In some embodiments, process 600 may further include step 641 , where the XR unit may call the AI ​​unit to process data 601 .

[0214] The XR unit may call the AI ​​unit to use AI technology to analyze and process data 601 in the extended reality service. For example, in a virtual-real fusion scenario, AI technology is used to analyze and predict data 601 (such as user feedback information).

[0215] Step 650, use the digital twin unit to process the data.

[0216] The digital twin unit can use the digital twin technology to process the data 601 to implement the digital twin service. In some embodiments, the digital twin unit can call the XR unit and / or the AI ​​unit to process the data 601 to implement the digital twin service.

[0217] Step 660, using the data flow unit to process the data.

[0218] The data circulation unit may process the data 601 using data circulation technology to implement data circulation services. For example, the data circulation unit may perform data privacy calculation and encryption processing on the data 601 to implement the security of data 601 in transmission, sharing and / or exchange across systems and / or medical institutions.

[0219] In some embodiments, process 600 may further include step 661 , processing the derived data using a data flow unit.

[0220] Derivative data refers to data generated in real time and dynamically in medical services. For example, derivative data may include data generated by XR units, AI units, digital twin units, etc. in the process of processing data 601 according to medical business needs. For example, it can be user feedback information (such as voice, text, etc.) obtained by the XR unit, or it can be the prediction result generated by the AI ​​unit, or it can be the processing result of the digital twin unit (such as patient diagnosis report, etc.). In some embodiments, the derivative data can also be persistently stored in the data lake 521 of the data lake warehouse 520 for use in subsequent medical business processing tasks. In some embodiments, the derivative data can also be cached in the cache area of ​​the data lake warehouse 520.

[0221] Furthermore, the data circulation unit may process the derived data according to actual needs to realize data circulation services.

[0222] It should be noted that different data processing units can process the same or different data in the data lake 521. In addition to the original data 601 collected by the hardware device, the data processing unit can also process other data stored in the data lake 521, including derived data, index data, etc.

[0223] In some embodiments of this specification, data is processed through XR units, AI units, digital twin units, and data circulation units, so that the hospital support platform can support new technologies that traditional hospitals cannot support (including XR technology, AI technology, digital twin technology, data circulation technology, etc.). Using these new technologies in medical business processing tasks can improve data processing efficiency and accuracy, thereby improving the quality of user services.

[0224] Figure 7 It is an exemplary schematic diagram of a method for storing data according to some embodiments of the present specification. Figure 7 The process 700 shown may be executed by a data processing layer (eg, a processing device therein).

[0225] Step 710 , determining evaluation information of data. The data refers to data acquired by the hardware of the hardware layer 310 and obtained via the interface layer 320 .

[0226] The evaluation information may include information obtained after evaluating various characteristics of the data (such as completeness, quality, security, size). For example, the evaluation information may include data integrity, which can be obtained by performing an integrity evaluation on the data. For example, it can be determined whether the data is missing data, whether key data is missing, or the proportion of missing data to determine the data integrity. Optionally, when the data integrity is lower (such as the proportion of missing data is higher than a threshold), a warning may be issued to reacquire the data. For another example, for image-type data, the data evaluation information may include the evaluation results of image quality (such as clarity, signal-to-noise ratio).

[0227] In some embodiments, the assessment information may include a security level of the data. The security level may be used to indicate the degree to which the data needs to be protected. The security level may be determined based on the sensitivity and importance of the data. In some embodiments, the security level may be related to whether the data contains the user's private information, sensitive information, or confidential information. If the data contains private information, sensitive information, or confidential data, the data has a relatively high security level.

[0228] In some embodiments, the evaluation information may include data volume and / or data collection frequency. The data volume is used to measure the size of the storage space occupied by the data within a preset time period (such as one day, one week). The data collection frequency is used to measure the number of times the data is collected within a preset time period. In some embodiments, the data processing layer 330 can determine the data volume and data collection frequency based on a data statistics method. For example, the data volume (such as maximum value, minimum value, average value, etc.) and data collection frequency (such as maximum number of times, minimum number of times, average number of times) of a preset time period can be counted to obtain the data volume and data collection frequency.

[0229] In some embodiments, the data processing layer 330 can also determine the data volume and / or data collection frequency of a certain type of data in the future period of time based on the evaluation model. The evaluation model can be a long short-term memory network (LSTM) model or other time series-based machine learning network model. Taking the data volume as an example, the input of the data volume evaluation model includes time series data, and the output includes the data volume in the future period of time. Among them, the time series data includes the historical data volume of this type of data in multiple historical time periods. The evaluation model can automatically predict the data volume and / or data collection frequency of various types of data in the future period of time, so as to better monitor the data.

[0230] In some embodiments, the evaluation information may include a data importance coefficient. The importance coefficient may reflect the importance of the data. The importance coefficient may be determined based on a combination of factors such as the degree of relevance of the data to the hospital's business, the likelihood of the data being used, the frequency of the data being used, and the security level of the data.

[0231] Step 720, determine a target storage strategy based on the evaluation information.

[0232] The target storage strategy refers to the way data is stored, including encrypted storage strategy, distributed storage strategy, etc. For example, for data with a higher security level (such as a security level exceeding a threshold), the encrypted storage strategy can be used as the target storage strategy, and the data can be encrypted and stored based on an encryption algorithm. For another example, when the data volume and / or data frequency corresponding to the data is greater than a threshold, it can be determined that the target storage strategy corresponding to the data is a distributed storage strategy. The distributed storage strategy can relieve the pressure on storage devices.

[0233] In some embodiments, the target storage policy may also include a storage period for the data. For example, the greater the importance coefficient, the longer the storage period.

[0234] Step 730, based on the target storage policy, store the data in the data lake.

[0235] Figure 8is an exemplary schematic diagram of the application development layer according to some embodiments of this specification. Figure 8 As shown, the application development layer 340 may include development tools 810 , an application market 820 , and a multi-tenant operation platform 830 .

[0236] Development tools 810 may include software development tools, libraries, and frameworks for developing, testing, and publishing applications. Development tools 810 may be used to simplify the development process, reduce coding work, and ensure that application developers can efficiently build software applications that are feature-rich, user-friendly, and maintainable. Development tools 810 may include APIs, sample code (demo source code), code development tools (such as code editors, debuggers, packaging and publishing devices, etc.), technical documentation, etc.

[0237] In some embodiments, various development resources may be provided to developers in the form of a software development kit (SDK). Figure 8 As shown, the development tool 810 may include an extended reality (XR) SDK, an artificial intelligence (AI) SDK, a digital twin SDK, etc. Different SDKs may include corresponding application programming interfaces and demonstration source codes. Developers (such as hospital developers and third-party developers) can download the desired SDK from the development tool 810 through the application development layer 340 according to their needs to develop applications. For example, developers can develop applications related to extended reality through the extended reality SDK.

[0238] The application market 820 is used to support online publishing, subscription, downloading, and trading of applications. Figure 8 As shown, the application market 820 may include multiple applications such as application 1, application 2, and application 3. Each application may be developed and / or updated by a developer using a development tool 810 and published to the application market 820. Users may download applications from the application market 820 and obtain corresponding user services using the downloaded applications.

[0239] In some embodiments, the applications in the application market 820 can be used to implement one or more user services in the service layer 350 (such as patient space services, medical space services, and management space services). Figure 8 As shown, the applications in the application market 820 may include the patient space application for patients, the medical space application for medical staff, and the management space application for management personnel in the service layer 350.

[0240] The multi-tenant operation platform 830 refers to a platform that provides operation services for multiple medical institutions. It can provide cross-campus operation, campus operation, department operation and other services for different medical institutions. Exemplary operation services include personnel management, cross-campus / department resource scheduling, campus / department evaluation, account authority management, etc. Figure 8 As shown, the multi-tenant operation platform 830 may include operation platforms corresponding to medical institution 1, medical institution 2, medical institution 1, etc.

[0241] In some embodiments, the application development layer 340 can be built based on a multi-tenant model. A multi-tenant model is a software architecture model that allows a single instance of a software application or database to serve multiple tenants (i.e., application developers, hospitals, healthcare organizations, or user groups).

[0242] In some embodiments, the application development layer 340 may be deployed on a cloud platform (such as a public cloud or a private cloud), and each tenant may have its own independent space and / or resources. For example, the operating platforms corresponding to different medical institutions (such as medical institution 1 and medical institution 2) are independent and isolated from each other.

[0243] In some embodiments, the application development layer 340 can provide open services for tenants. Open services may include resource access services, etc. Resources may include, but are not limited to, development resources provided by the application development layer, resources and data of other tenants (such as workspaces of other tenants, data of the operation platform), etc. In some embodiments, tenants can set permissions for their own resources and / or data, for example, select some resources to share or open to other tenants. When the application development layer 340 provides open services for tenants, it is necessary to consider the permission information of other tenants.

[0244] In some embodiments of the present specification, the application development layer 340 constructed by the multi-tenant architecture enables each tenant to operate logically independent data sets and ensure that these data sets do not interfere with each other. By introducing the multi-tenant architecture, basic equipment such as servers, storage devices and network resources to achieve resource sharing among multiple tenants, each tenant can customize the configuration, interface and function to meet their specific needs without affecting other tenants.

[0245] Some embodiments of this specification also provide a hospital support platform, including: hardware equipment, configured to collect data related to hospital business; software and hardware interfaces, configured to obtain data from the hardware equipment and send it to a data center for storage; processing equipment, configured with a data processing unit for data processing; user space applications, configured to provide users related to hospital business with user services related to hospital business, wherein the user services are implemented by the processing equipment through processing at least a portion of the data stored in the data center. Optionally, the hospital support platform may also include an open interface, configured for developers to call at least a portion of the data processing unit and use at least a portion of the data processing unit for application development.

[0246] Some other embodiments of the present specification also provide a hospital support platform, including: hardware equipment, configured to collect data related to hospital business; software and hardware interfaces, configured to obtain data from the hardware equipment and send it to the data center for storage; processing equipment, configured with a data processing unit for data processing; open interfaces, configured for developers to call at least a part of the data processing unit, and use at least a part of the data processing unit for application development. Optionally, the hospital support platform may also include a user space application, configured for users related to the hospital business to obtain user services related to the hospital business, wherein the user services are implemented by the processing device through processing at least a part of the data stored in the data center.

[0247] Some other embodiments of the present specification also provide a hospital support platform, including hardware equipment, configured to collect data related to hospital business; a data lake, configured to store data persistently in a tamper-proof manner; a processing device, configured with a data processing unit for data processing, the data processing unit includes an extended reality (XR) unit, an artificial intelligence (AI) unit, a digital twin unit and a data circulation unit; a user space application, configured to provide users related to hospital business with user services related to hospital business, wherein the user service is implemented by the processing device by processing at least a portion of the data stored in the data center. In some embodiments, processing at least a portion of the data includes mapping the at least a portion of the data to a virtual hospital using at least a portion of the data twin unit, the AI ​​unit and the XR unit; the user space application is further configured for the relevant users to interact with the virtual hospital so that the relevant users obtain at least a portion of the user services. For example, the digital twin unit can update the digital twin in the virtual hospital based on the at least a portion of the data; the AI ​​unit can update the intelligent body in the virtual hospital based on the at least a portion of the data; the XR unit can update and render the image data corresponding to the virtual hospital based on at least a portion of the data. In some embodiments, when a user interacts with the virtual hospital, the XR unit is configured to use XR technology to present at least a portion of the virtual hospital to the relevant user (e.g., superimposed on the relevant user's real-world field of view based on MR technology). For more information about the virtual hospital, please refer to Figure 1 Related description.

[0248] Fig. 9A Schematic diagram is a schematic diagram of 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 the patient by conducting preliminary inquiries to the patient before the patient enters the consulting room for a formal consultation. Specifically, while the patient is waiting for consultation, 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, and 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 900A is executed by a pre-consultation agent configured on the processing device 210 that corresponds to the pre-consultation service.

[0249] Step 910, determine the inquiry content of the pre-consultation inquiry based on the department of the doctor (eg, the patient's registered doctor).

[0250] The pre-consultation inquiry is used to conduct preliminary inquiries to the patient before the formal consultation. The pre-consultation inquiry may include multiple rounds of inquiries. The inquiry content may include the inquiry content of each round of inquiry. Alternatively, the inquiry content only includes the inquiry content of the first round of inquiry. In some embodiments, the processing device 210 may obtain a pre-consultation record template corresponding to the doctor's department, and determine the inquiry content according to the pre-consultation record template.

[0251] In some embodiments, the processing device 210 may obtain known information about the patient (e.g., electronic medical records, chief complaint, etc.), and determine missing information that has not been collected in the pre-consultation record template by comparing the pre-consultation record template with the known information. In addition, the processing device 210 may determine the inquiry content based on the missing information.

[0252] In some embodiments, the processing device 210 may use an inquiry model to determine the inquiry content based on the known information of 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 the known information of the doctor's department and the patient. The first inquiry content determination model is configured to output the inquiry content based on the patient's missing information.

[0253] Step 920: Based on the inquiry content, control the patient terminal to conduct a pre-diagnosis inquiry on the patient.

[0254] In some embodiments, after the patient registers with the doctor, the processing device 210 may determine the estimated waiting time for the patient to receive the medical consultation service. For example, the estimated waiting time may be the time difference between the current time and the patient's registration time. For another example, the estimated waiting time may be determined based on the doctor's consultation record of the day and the patient's registration record. The doctor's consultation record of the day is a record reflecting the doctor's outpatient situation on the day.

[0255] In some embodiments, in response to determining that the estimated waiting time is greater than the first preset time threshold, the processing device 210 can enable the patient's terminal to initiate a pre-consultation inquiry to the patient or display a suggestion for a pre-consultation. This approach can ensure that there is sufficient time for the pre-consultation and avoid the doctor calling the patient during the pre-consultation process.

[0256] In some embodiments, in response to determining that the estimated waiting time is less than a second preset time threshold, the processing device 210 may cause the patient's patient terminal to initiate a pre-consultation inquiry to the patient or display a suggestion for a pre-consultation inquiry. The second preset time threshold may be greater than the first preset time threshold. For example, when it is detected that the current time is less than 24 hours from the registration time period (i.e., the estimated waiting time is less than 24 hours), the patient terminal may display a suggestion for a pre-consultation inquiry to the patient (e.g., by making a suggestion to the patient through a virtual character), thereby promptly reminding the patient to conduct a pre-consultation inquiry.

[0257] In some embodiments, the processing device 210 may detect that the patient initiates a pre-consultation inquiry request through the patient terminal, and then enable the patient terminal of the patient to conduct a pre-consultation inquiry on the patient.

[0258] In some embodiments, the patient terminal can present a virtual character to conduct a pre-interview inquiry based on the inquiry content. A virtual character refers to a digital character with specific characteristics (e.g., specific appearance characteristics, sound characteristics, etc.), and can communicate with the patient to conduct a pre-interview with the patient. Specifically, the processing device 210 can display the virtual character through the screen of the patient terminal (e.g., an XR device) and play the inquiry content through the sound output device of the patient terminal. At the same time, the virtual character can simulate human language expressions, gestures, etc. to provide patients with a realistic communication experience. In some embodiments, the virtual character can be a visual representation of a pre-interview agent.

[0259] In some embodiments, the virtual character may have a preset appearance feature. In some embodiments, the appearance feature of the virtual character may be determined based on the optical image data of the doctor with whom the patient is registered. In some embodiments, the virtual character may determine the appearance feature of the virtual character based on the basic information of the patient. In some embodiments, the processing device 210 may select a suitable virtual character from the virtual character library as the virtual character based on the appearance feature of the doctor and / or the basic information of the patient.

[0260] In some embodiments, the pre-consultation inquiry may include multiple rounds of inquiry. The pre-consultation content may include the inquiry content of each round of inquiry in the pre-consultation inquiry. The pre-consultation inquiry may include the inquiry content of each round of inquiry in the pre-consultation inquiry. Fig. 9B The process 900B shown in is executed.

[0261] like Fig. 9B As shown, for the first round of queries, the processing device 210 may enable the patient terminal to perform the first round of queries based on the corresponding query content.

[0262] For each current round of inquiries (referred to as the current inquiry for short) except the first round of inquiries, the processing device 210 can adjust the inquiry content of the current inquiry (referred to as the current inquiry content for short) based on the reference data collected before the current inquiry, so that the inquiry content is more in line with the patient's condition. Specifically, the processing device 210 can determine the semantic information and emotional information of the patient's historical answers based on the reference data collected before the current inquiry. The reference data may include voice signals, image data, text data, etc. collected by the patient terminal. The historical answer is the patient's answer to the inquiry content of the historical round.

[0263] The semantic information of the historical answer characterizes the content of the historical answer. The emotional information of the historical answer may indicate the patient's emotion when providing the historical answer (e.g., calm, nervous, anxious, afraid, suspicious, irritable, etc.). The processing device 210 may determine the semantic information by performing text transcription, speech content recognition, etc. on the reference data. The processing device 210 may determine the emotional information by analyzing the content, tone, intonation, speech speed, etc. of the reference data.

[0264] Continue to refer Fig. 9B , the processing device 210 can adjust the current inquiry content based on semantic information and emotional information. For example, when the patient's emotional information is "nervous" or "afraid", the processing device 210 can add soothing words to the current inquiry content. For another example, when the semantic information indicates that the patient has not clearly answered the historical inquiry, the processing device 210 can adjust the current inquiry content to repeat the historical inquiry, thereby guiding the patient to clearly answer the historical inquiry. The originally determined current inquiry content can be used as the inquiry content of the next round of inquiries. In this way, the current consultation content can be adjusted in time according to the patient's condition, thereby improving the service quality of the pre-consultation.

[0265] In some embodiments, in addition to adjusting the current inquiry content, the sound features used for the inquiry can also be adjusted in real time based on the patient's condition. Sound features include speech rate features, tone features, intonation features, volume features, etc. Fig. 9B As shown, the processing device 210 can determine the voice characteristics of the current inquiry based on the semantic information and emotional information of the patient's historical answers, and make the patient terminal adjust the current inquiry based on the adjusted inquiry content and the voice of the current inquiry. This method can better take into account the emotional changes of the patient, thereby enhancing the anthropomorphic effect of the virtual character and improving the quality of the pre-consultation service.

[0266] In some embodiments, Fig. 9BAs shown, the processing device 210 can further obtain the patient's physiological state information. The patient's physiological state information can reflect the patient's real-time physiological state. The physiological state information 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 expression, muscle state, etc. In some embodiments, the patient's physiological state information can be obtained through a wearable device worn by the patient or an image sensor in the patient's environment.

[0267] In addition, the processing device 210 can adjust the current query content based on the semantic information, the emotional information and the physiological state information. Specifically, the processing device 210 can update the patient's emotional information according to the patient's physiological state information. It is understandable that the patient's inner emotions may not always be fully expressed through the patient's answer, so the patient's emotional information may be updated or modified according to the patient's physiological state information. In addition, the processing device 210 can adjust the current query content according to the semantic information and the updated emotional information.

[0268] In some embodiments of the present 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 the current inquiry content adjustment, and further improving the service quality of the pre-consultation service.

[0269] like Fig. 9B As shown, in some embodiments, the processing device 210 can determine feedback parameters based on at least a portion of the semantic information, emotional information, and physiological state information, and control the wearable device to apply feedback to the patient based on the feedback parameters. The feedback may include at least one of force feedback or temperature feedback. The feedback parameters can be used to control the manner in which feedback is applied, such as the type of feedback, the part of the body to which feedback is applied, the intensity of feedback, and the like. In some embodiments, the processing device 210 can determine the patient's emotions and emotional levels based on at least a portion of the semantic information, emotional information, and physiological state information, and determine the feedback parameters based on the emotions and emotional levels. This method can soothe the patient's negative emotions in a timely manner, thereby improving the quality of pre-consultation services.

[0270] In some embodiments, the processing device 210 may end the pre-consultation inquiry according to a preset condition. The preset condition may be that the amount of remaining missing information is 0. The preset condition may also be that the time difference between the patient's current time and the estimated waiting time is less than a threshold.

[0271] In some embodiments, the inquiry content determined in step 910 may only include the inquiry content of the first round of inquiries. The current inquiry content of each current inquiry except the first round of inquiries may be determined during the pre-inquiry process. For example, in the current inquiry, the processing device 210 may input the inquiry content of the historical inquiry, 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.

[0272] Step 930 : generating a pre-consultation record based on the reference data collected by the patient terminal during the pre-consultation inquiry.

[0273] The reference data may include voice data, text data, image data, etc. input by the patient through the patient terminal during the pre-consultation inquiry. The pre-consultation record may be used to record the patient information collected during the pre-consultation inquiry. Optionally, some known information of 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 a template set by the doctor.

[0274] For example, when the reference data includes a speech signal, the processing device 210 may first transcribe the speech signal into text, and extract keywords from the text through a keyword extraction algorithm. In addition, the processing device 210 may convert the keywords into medical terms. In addition, the processing device 210 may obtain multiple template fields in the pre-consultation record template, retrieve the content corresponding to each template field from the medical terminology, and fill it into the corresponding position of the pre-consultation record template. The conversion of keywords may be performed based on a term conversion model or based on a knowledge dictionary. The term conversion model may be configured to convert spoken descriptions into medical terms.

[0275] In some embodiments, the pre-consultation inquiry may be performed via a terminal device other than the patient terminal (eg, a waiting terminal).

[0276] Fig.10 1000 is a schematic diagram of an exemplary process for providing medical outpatient services based on perception information according to some embodiments of the present specification. Schematic diagram of medical consultation service. In some embodiments, process 1000 may include one or more of subprocesses 1010, 1020, 1030, and 1040. In some embodiments, at least a portion of process 1000 is performed by a consultation agent corresponding to the medical consultation service configured on the processing device 210.

[0277] During the consultation phase, the patient can communicate with the registered doctor to receive consultation services (for example, on-site consultation services in the clinic, remote consultation services). In some embodiments, user services related to the consultation phase can be provided to relevant users (such as doctors, patients, and remote companions) through at least one terminal device. At least one terminal device includes a public terminal device in the clinic, a patient terminal device, a doctor terminal device, a terminal device of a remote companion, and the like. The public terminal device in the clinic refers to a terminal device installed on-site in the clinic, which may include a display device, a sound output device, a sound sensor, an XR device, a wearable device, or the like, or any combination thereof. Perception information can be collected by perception devices in the environment where the patient, doctor, or remote companion is located during the consultation process. The perception device can be an independent device or a part of at least one terminal device.

[0278] Subprocess 1010 may be used to provide consultation advice based on the perceived information. Subprocess 1010 may be performed during the consultation phase. Fig.10 As shown, subprocess 1010 may include step 1012 and step 1014 .

[0279] Step 1012, generating a consultation suggestion based on the sensed information and the patient data of the patient. Consultation suggestions refer to suggestions to assist doctors in providing medical consultation services. Exemplarily, consultation suggestions may include supplementary inquiry suggestions, physical examination suggestions, prescription suggestions, treatment plan suggestions, etc.

[0280] In some embodiments, the consultation suggestion may be determined based on the knowledge database, consultation specifications, etc. corresponding to the registration department. For example, the processing device 210 may 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 specifications, etc. based on the conversation content and / or patient data to determine the consultation suggestion. As an example only, the consultation specification may be searched based on the conversation content and / or patient data to determine which information in the consultation specification has not been collected, and provide supplementary inquiry suggestions based on this information.

[0281] In some embodiments, the consultation recommendation can be generated based on the diagnosis model. Specifically, the processing device 210 can determine the model input based on the perceived sensory information and the patient data, input the model input into the diagnosis model, and the diagnosis model can output the corresponding consultation recommendation. For example, the model input can include patient data, conversation content determined based on voice signals, patient status information determined based on image data, etc., or any combination thereof.

[0282] In some embodiments, the consultation recommendations may be generated by a consultation agent. The consultation agent may learn a generation mechanism for generating consultation recommendations from various data (e.g., historical consultation records, knowledge databases, and consultation specifications), and process the perception information and patient data according to the mechanism to provide consultation recommendations.

[0283] Step 1014, controlling at least a portion of at least one terminal device to present a medical consultation recommendation.

[0284] For example, when a patient receives on-site medical outpatient services in a clinic, the processing device 210 can control the public terminal device or the doctor's terminal to present medical advice. For another example, when a patient receives remote medical outpatient services, the processing device 210 can control the doctor's doctor terminal and the patient's patient terminal to present medical advice respectively. Medical advice can improve the accuracy of diagnosis and prescription, and improve the efficiency of medical consultation services.

[0285] Subprocess 1020 may be used to generate a target diagnosis record based on the perception information. Subprocess 1020 may be executed at the end of the consultation session. Fig.10 As shown, subprocess 1020 may include steps 1022 , 1024 , and 1026 .

[0286] Step 1022, generating an initial diagnosis record based on the perception information.

[0287] The initial diagnosis record may be an automatically generated diagnosis record. In some embodiments, the initial diagnosis record may include an initial patient medical record, an initial diagnosis opinion, an initial diagnosis prescription (e.g., an initial treatment prescription and an initial examination prescription), an initial doctor's order, etc. In some embodiments, key content may be extracted from the perceived information based on a diagnosis record template. Key content refers to content related to a template field in a diagnosis record template. Key content may be converted into professional content based on a knowledge dictionary or a term conversion model. Further, the diagnosis record template may be updated based on professional content and a knowledge database to generate an initial diagnosis record. The knowledge database refers to a knowledge database of a registration department, for example, including the department's consultation specifications (e.g., disease description specifications, diagnosis specifications, prescription specifications, doctor's order specifications, etc.).

[0288] In some embodiments, physical examination data of a patient collected by one or more examination devices in an outpatient process may be obtained, and an initial diagnosis record may be further generated based on the physical examination data. In some embodiments, the initial diagnosis record may be generated by a medical inquiry agent. The medical inquiry agent may learn a mechanism for generating a diagnosis record from various data (e.g., a diagnosis record template, a knowledge dictionary, a knowledge database, etc.), and process the perception information and patient data according to the learned mechanism to generate a diagnosis record.

[0289] Step 1024, present the initial diagnosis record to the doctor.

[0290] For example, when a patient begins a consultation, the processing device 210 may control the public terminal to present an initial diagnosis record. As another example, the processing device 210 may control the doctor terminal to present the initial diagnosis record to the doctor. In some embodiments, the doctor terminal may present the initial diagnosis record to the doctor at a preset time (e.g., after the doctor finishes the consultation work for the day).

[0291] Step 1026, generating a target diagnosis record based on the initial diagnosis record and the feedback information input by the doctor on the initial diagnosis record.

[0292] The feedback information input by the doctor may include the doctor's modification and / or confirmation of the initial diagnosis record. The target diagnosis record refers to the diagnosis record modified and / or confirmed by the doctor. In some embodiments, the target diagnosis record may include the target patient medical history, target diagnosis opinion, target diagnosis prescription (e.g., target treatment prescription and target examination prescription), target doctor's order, etc.

[0293] By generating target diagnosis records, on the one hand, it is possible to reduce manual writing errors in target diagnosis records and improve the efficiency of generating target diagnosis records. On the other hand, it is possible to reduce the paperwork of doctors, allowing them to devote more energy to caring for patients, thereby improving the quality of medical outpatient services.

[0294] Sub-process 1030 can be used to provide remote medical accompaniment services based on the perception information. The patient can initiate a request for remote medical accompaniment services before the consultation. Sub-process 1030 can be executed during the consultation phase. Fig.10 As shown, subprocess 1030 may include step 1032 and step 1034 .

[0295] Step 1032, based on the sensed information, determine whether the patient needs to communicate with the remote patient companion.

[0296] In some embodiments, the processing device 210 can detect whether the patient has issued a request to communicate with the remote accompanying person based on the perception 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 perception information, and determine whether the patient needs to communicate with the remote accompanying person 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 the remote accompanying person.

[0297] When it is determined that the patient needs to communicate with the remote patient companion, the processing device 210 may execute step 1034 .

[0298] Step 1034, controlling at least a portion of at least one terminal device to enlarge the interface element.

[0299] When the patient receives on-site medical consultation services in the clinic, the processing device 210 can control the public terminal device to enlarge the interface elements. When the patient receives remote medical consultation services, the processing device 210 can control the patient terminal of the patient to enlarge the interface elements. Through the enlarged interface elements, the patient can view the real-time image of the remote accompanying person and better communicate with the remote accompanying person.

[0300] In some embodiments, when a patient receives on-site medical consultation services in a clinic, when it is detected that the patient needs to communicate with a remote accompanying person, the processing device 210 can remind the patient to wear an XR device and control the XR device to present image data of the remote accompanying person.

[0301] In some embodiments of the present specification, the patient's communication needs can be detected based on the sensory information, and the communication needs can be met in a timely manner, thereby providing the patient with more humane care and a more realistic and immersive companionship experience.

[0302] Subprocess 1040 may be used to present medical data to a target user based on the perceived information. Fig.10 As shown, subprocess 1040 may include step 1042 and step 1044 .

[0303] Step 1042: Based on the perception information, obtain a control instruction issued by at least one target user to retrieve at least a portion of the medical data.

[0304] The target user may include at least a patient and a doctor. In some embodiments, the target user may also include a remote patient companion. The patient's medical data may include various data reflecting the patient's health status (e.g., electronic medical records, medical images, medical examination results, etc.).

[0305] A control instruction is an instruction for retrieving at least a portion of medical data (e.g., an electronic medical record) for display. For example, a control instruction can be used to retrieve a three-dimensional model of an organ of interest of a patient in an electronic medical record for display. In some embodiments, the control instruction can be used to set display parameters (e.g., display angle, display size, or display position). In some embodiments, the control instruction can also be used to annotate key data on medical data (e.g., a three-dimensional model of an organ of interest).

[0306] In some embodiments, the perception information may include a voice signal collected by a sound sensor, and the control instruction may be obtained by performing semantic analysis on the voice signal. In some embodiments, the target user may issue a control instruction by saying a preset wake-up word. In some embodiments, the perception information may include optical image data of the target user (e.g., a patient and / or a doctor) collected by an image sensor, and the control instruction may be obtained by performing gesture recognition on the target user in the optical image data. In some embodiments, the target user may issue a control instruction using a control device (e.g., a remote control, a smart control glove, etc.).

[0307] In some embodiments of the present specification, the target user can flexibly adjust the display content and / or display parameters, for example, through voice, gestures, etc., so as to optimize the user experience and improve the efficiency of the medical consultation service.

[0308] Step 1044, in response to the control instruction, retrieve at least a portion of the medical data and present at least a portion of the medical data through at least one terminal device.

[0309] For example, the processing device 210 may retrieve at least a portion of the medical data from the storage device and control at least one terminal device to present at least a portion of the medical data. When the control instruction includes a display parameter, the processing device 210 may control at least one terminal device to present at least a portion of the medical data based on the display parameter.

[0310] In some embodiments of the present 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 the medical data on different terminal devices, which helps to improve the communication efficiency of the target users and enhance the interactivity of the medical treatment process.

[0311] Fig.11 11 is a schematic diagram of an exemplary process for providing services to relevant users in the hospital admission process according to some embodiments of this specification. In the hospital admission process, patients can go through relevant procedures to be admitted to the hospital. In some embodiments, at least a portion of process 1100 is performed by an inpatient agent corresponding to the inpatient service configured on the processing device 210. In some embodiments, at least a portion of process 1100 (e.g., steps 1130-1150) is performed by a nursing agent corresponding to the nursing service configured on the processing device 210.

[0312] In step 1110 , the processing device 210 may guide the patient to a ward.

[0313] For example, the processing device 210 may instruct the patient's patient terminal to guide the patient to the ward. For example, in response to the hospitalization guidance request, the processing device 210 may obtain the first location of the patient's patient terminal and the second location of the ward, and determine the planned route from the first location to the second location based on the real-time map of the hospital. Then, the processing device 210 may instruct the patient terminal device to present guidance information related to the planned route to the patient.

[0314] Step 1120, provide admission education information to the patient.

[0315] The admission education information may be used to introduce admission information (e.g., admission procedures, admission operations, pre-admission fees, payment methods, etc.), admission and hospitalization rules, hospital environment, the patient's doctor and / or nurse, etc. to the patient. In some embodiments, the processing device 210 may cause the patient terminal device (e.g., the XR device 260-2) to present a virtual character that provides the admission education information.

[0316] At 1130, the processing device 210 may assist the nurse in preparing for admission.

[0317] The admission preparation may be performed by a nurse to prepare hospital supplies for the patient. In some embodiments, the processing device 210 may present the patient's admission notice through the nurse terminal 1105 in the nurse workstation or the smart nursing cart 240-4 to assist the nurse in performing the admission preparation. The admission notice may include the patient's patient data, the patient's hospital supplies list, the patient's ward information, the patient's initial examination information, etc.

[0318] The admission checkup, also known as the inpatient checkup, can be performed after the patient is admitted to the ward. The admission checkup can be used to collect information about the patient's current medical condition (e.g., vital signs, basic health data, etc.). The initial checkup may include blood pressure, blood sugar, heart rate, temperature, or similar items, or any combination thereof.

[0319] In step 1140, the processing device 210 may issue a reminder to perform an admission check. The reminder may include a message reminder, a sound reminder, a pop-up reminder, etc. For example, the processing device 210 may instruct the nurse terminal 1105 or the smart nursing cart 240-4 to present the reminder.

[0320] In some embodiments, the processing device 210 may determine whether the patient meets the conditions for admission examination in the ward based on the sensing information collected by the sensing device in the ward. The condition for admission examination in the ward may include that the patient has arrived in the ward for a period of time. If the patient meets the conditions, the processing device 210 may issue a reminder for admission examination.

[0321] In step 1150, the processing device 210 may guide the nurse to the ward. In some embodiments, the processing device 210 may control the movement of the smart nursing cart 240-4 to guide the nurse to enter the ward.

[0322] Step 1160, conduct admission examination for the patient.

[0323] For example, after the nurse arrives at the ward, one or more examination devices may be used to perform 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 may 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 may present an admission examination diagram, the patient's electronic medical record, etc.

[0324] In step 1170 , the processing device 210 generates an admission record.

[0325] Admission records refer to records showing that a patient has been admitted to a ward and / or the status of the patient when admitted to the ward. Admission records may include admission information (e.g., admission number, clinical information, admission time, pre-paid hospitalization fee amount, payment method, etc.), physical examination data collected during admission examination, etc.

[0326] In some embodiments, the processing device 210 may generate an admission record based on the admission record template and the physical examination data. In some embodiments, the processing device 210 may further generate an admission record based on the patient's electronic medical record. In some embodiments, the processing device 210 may present the admission record to the nurse based on the smart nursing cart 240-4 or the nurse terminal 1105, and generate a target admission record based on the admission record and feedback information of the admission record input by the nurse through the smart nursing cart 240-4 or the nurse terminal 1105. The feedback information may include a confirmation instruction, a modification instruction, etc. input by the nurse.

[0327] In some embodiments of the present specification, admission services can be provided to patients in a semi-automated manner with the assistance of a medical service system (e.g., smart nursing cart 240-4) and / or an intelligent agent, thereby reducing labor costs and improving the efficiency of admission services.

[0328] Fig.12 12 is a schematic diagram of a process for providing nursing services according to some embodiments of the present specification. In some embodiments, process 1200 may be performed every day during the patient's hospitalization to provide nursing services to the patient. In some embodiments, at least a portion of process 1200 may be performed by an inpatient agent corresponding to the inpatient service configured on the processing device 210. In some embodiments, at least a portion of process 1200 may be performed by a nursing agent corresponding to the nursing service configured on the processing device 210.

[0329] In step 1202, the processing device 210 determines a daily plan for the patient based on the patient data of the patient and the doctor's instructions to the patient.

[0330] The doctor's orders to the patient refer to the doctor's instructions or instructions to the patient. In some embodiments, the patient's orders can be stored in a storage device and can be updated when any doctor issues a new order for the patient. The processing device 210 can obtain the latest version of the orders from the storage device. In some embodiments, the processing device 210 can monitor various hardware devices to detect whether the patient's orders are updated. For example, when providing admission inquiry services and / or ward rounds services to the patient, the patient's doctor can issue new orders to the patient. The processing device 210 can detect new orders based on the sensing information collected by the sensing device during the admission inquiry service and / or ward rounds service. Once the new orders are detected, the new orders can be stored in the storage device. As another example, the doctor can update the orders in the storage device through the doctor's terminal. In some embodiments, the processing device 210 can determine the doctor's orders based on the patient's electronic medical record.

[0331] In some embodiments, the processing device 210 can determine the patient's daily plan based on the patient's patient data and the patient's doctor's orders. The daily plan may include at least one medical operation that needs to be performed on the patient that day. Exemplarily, the medical operation may include a nursing operation, an inspection operation, etc.

[0332] In step 1204 , the processing device 210 may present the daily plan to the patient via a public terminal device in the ward (eg, the bedside terminal 240 - 6 ).

[0333] In step 1206 , the processing device 210 may present the daily plan to the nurse corresponding to the patient through a nurse terminal (eg, a terminal device in a nurse workstation, etc.).

[0334] Step 1208: When the daily plan includes at least one nursing operation, the nurse may perform at least one nursing operation on the patient, and the processing device 210 may assist the nurse in performing at least one nursing operation according to the daily plan.

[0335] like Fig.12As shown, for each of at least one nursing operation, the processing device 210 can control the intelligent nursing cart to guide the nurse to the ward to perform the nursing operation according to the scheduled time of the nursing operation. For example, before the scheduled time of the nursing operation, the intelligent nursing cart can be controlled to move to the nurse's workstation to notify the nurse that the nursing operation needs to be performed for the patient. Then, the intelligent nursing cart can be controlled to move and guide the nurse to the patient's ward. The processing device 210 can further control the intelligent nursing cart to present nursing instructions for the nursing operation after the nurse arrives at the ward.

[0336] At step 1210 , the processing device 210 may generate a care record.

[0337] Nursing records refer to nursing operation records applied to patients and / or patient status (e.g., vital signs and other physiological measurements) before, after, or during nursing operations. In some embodiments, the processing device 210 can obtain sensory information collected by one or more sensory devices in the ward when performing at least one nursing operation, and generate nursing records based on the sensory information. In some embodiments, the nursing record can be displayed to the nurse for confirmation via a smart nursing cart or a nurse terminal device.

[0338] In some embodiments of the present specification, the automatic 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. In addition, monitoring of doctor's order updates ensures timely updates of daily plans. This proactive approach ensures timely adjustments to interventions and nursing plans based on the latest doctor's orders, thereby improving nursing effectiveness and quality.

[0339] Fig.13 13 is an exemplary schematic diagram of a preoperative guidance process according to some embodiments of the present specification. In some embodiments, at least a portion of process 1300 may be executed by a surgical agent corresponding to a surgical service configured on the processing device 210.

[0340] Preoperative instructions may include patient escort, patient confirmation, preoperative education, preoperative cleansing, establishment of intravenous access, etc. Patient escort refers to the transportation of the patient from his / her current location to the waiting area of ​​the operating room.

[0341] Patient verification refers to verifying whether the patient meets the surgical criteria. For example, patient verification may include: verifying whether the identity information of the verification subject matches the target patient for the current surgical procedure; verifying whether the surgical procedure of the verification subject is currently scheduled; and verifying whether the current physical condition of the verification subject meets the requirements of the surgical procedure. It is understood that if the verification subject does not meet any of the surgical criteria, the patient's surgical procedure may be postponed or delayed.

[0342] 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. Fig.13 As shown, after the patient is transported to the waiting area 1310, the processing device 210 can collect the biometric information of the patient 261 through one or more sensing devices 1311 (e.g., image acquisition device, microphone, fingerprint sensor, etc.) in the waiting area 1310, and verify the identity of the patient 261 based on the biometric information. In some embodiments, the processing device 210 can use a nurse agent to verify the identity of the patient. For example, the nurse agent can verify the collected biometric information, or verify the identity of the patient through voice interaction with the patient (e.g., asking the patient's age, name, gender, etc.).

[0343] Preoperative care can include preoperative comfort and preoperative education. Preoperative comfort refers to preoperative preparations, which help patients reduce negative emotions (e.g., anxiety, tension, fear, etc.) through verbal communication, videos, music, etc. Preoperative education refers to preoperative preparations, which help patients understand the surgical procedure. Preoperative cleaning refers to preoperative preparations, such as body cleaning, hair removal (e.g., hair, body hair, etc.), and patients wearing surgical gowns. Establishment of intravenous access refers to establishing an intravenous access in the patient for drug injection to ensure that the drug can be effectively delivered to the patient during the operation.

[0344] In some embodiments, the processing device 210 may 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. Fig.13 As shown, before performing a preoperative operation on the patient according to the surgical plan, the processing device 210 can determine a planned path from the current location of the patient 261 (e.g., the ward 1303) to the waiting area 1310. The processing device 210 can control the smart wheelchair 240-5 to transport the patient 261 from the ward 1303 to the waiting area 1310 along the planned path.

[0345] In some embodiments, the processing device 210 may determine a planned path 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 role. 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.

[0346] In some embodiments, the processing device 210 can determine the patient's preoperative care materials based on the patient data and the surgical plan. During the process of transporting the patient to the waiting area, the processing device 210 can use the patient terminal to provide preoperative education to the patient based on the preoperative care materials. The preoperative care materials may include videos, music, images, texts, and other materials related to surgical explanations and / or emotional relaxation.

[0347] In some embodiments, the processing device 210 may use a nurse agent to provide preoperative education to the patient. Fig.13 As shown, the processing device 210 can present a virtual nurse character 1323 on the XR device 260-2 worn by the patient 261, and the virtual nurse character 1323 explains the preoperative care materials to the patient 261. In some embodiments, the virtual nurse character 1323 can interact with the patient 261 by voice to relieve 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 relieve the patient's emotions by collecting the patient's facial expressions, physiological signs, tone of voice, etc.

[0348] In some embodiments, the processing device 210 may use a nurse agent to guide a nurse in performing preoperative cleaning and / or establishing intravenous access.

[0349] In some embodiments, during the process of transporting the patient to the waiting area, the processing device 210 may obtain sensing information related to a portion of the planned path from the current position of the smart wheelchair to the waiting area (e.g., a portion of the planned path that the smart wheelchair has not yet traveled) through one or more sensing devices in the hospital (e.g., image sensor 1313). Based on the sensing information, the processing device 210 may determine the potential risk in the untraveled portion of the planned path, and update the untraveled portion based on the potential risk.

[0350] In some embodiments of the present specification, through the above-mentioned preoperative guidance process, a humanized, transparent and efficient preoperative preparation process can be provided, and preoperative preparation items can be dynamically adjusted according to patient feedback to improve the efficiency of preoperative preparation. Through the above-mentioned process of transporting patients and verifying patient identities, human errors are avoided and the safety of the entire surgical process is improved. Using virtual nurse images to assist in completing many preoperative preparation tasks can save labor costs.

[0351] Fig.14 1400 is a schematic diagram of a surgical execution process according to some embodiments of the present specification. The surgical execution process 1400 may include preoperative preparation, intraoperative matters, and postoperative matters. In some embodiments, at least a portion of the process 1400 may be executed by a surgical agent corresponding to a surgical service configured on the processing device 210. Fig.14As shown, preoperative preparation (eg, steps before performing an operation) may include step 1411 , step 1413 , and step 1415 .

[0352] Step 1411, activate the operating room.

[0353] Activating the operating room may include opening the operating room door, activating surgical equipment in the operating room, monitoring equipment, adjusting parameters in the operating room, verifying the status of surgical equipment, etc. 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 the scheduled time of the operation and adjust the indoor temperature, humidity and air quality.

[0354] Step 1413, prepare surgical tools.

[0355] The surgical tools may include surgical instruments and surgical consumables. In some embodiments, the processing device 210 may control the intelligent robotic nurse to prepare the surgical tools in the operating room before the operation according to the surgical plan. In some embodiments, the processing device 210 may further control the intelligent robotic nurse to disinfect the operating table and arrange the operating table (e.g., arrange the positions of various surgical tools on the operating table).

[0356] Step 1415, patient confirmation and / or patient anesthesia. Patient confirmation refers to confirming the identity of the patient. Patient anesthesia refers to administering anesthesia to the patient.

[0357] Step 1420, perform the surgical procedure. In some embodiments, Fig.14 As shown, matters during a surgical procedure (eg, intraoperative matters) may include remote collaboration, tool transfer, image interaction, intraoperative planning and navigation, and real-time alerts.

[0358] Telecollaboration refers to remote participation and / or remote guidance during surgical procedures.

[0359] Tool delivery refers to the delivery of surgical tools to the operator during surgery. In some embodiments, the processing device 210 can identify instructions for target surgical tools issued by the surgical participant based on the first sensing information collected by one or more first sensing devices in the operating room during surgery. Based on these instructions, the processing device 210 can control the intelligent robot nurse to deliver the target surgical tool to the surgical participant.

[0360] Image interaction refers to displaying the patient's digital human body model (e.g., a three-dimensional anatomical model of the surgical site), the patient's electronic medical records, the surgical plan of 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 patients through interactive devices in the operating room (e.g., display screens in the operating room, doctor's terminal device 270).

[0361] Intraoperative planning and navigation refers to the process of fusing a patient's lesion image (e.g., a CT scan image of the lesion) with the patient's digital body model, projecting the lesion image onto the patient's body, or superimposing the positioning and tracking of surgical tools to guide surgical participants during surgery.

[0362] Real-time alarms may include behavioral alarms of surgical participants, patient vital signs alarms, and equipment operating status alarms. Behavioral alarms refer to the monitoring and alarms of surgical participants' intraoperative operating behaviors. When a patient's vital signs (e.g., electrocardiogram, blood pressure, etc.) are abnormal, the patient's vital signs alarm may be activated. Equipment operating status alarms refer to alarms issued when surgical equipment is in an abnormal operating state.

[0363] like Fig.14 As shown, the process after the operation is performed (e.g., post-operative matters) may include steps 1431, 1433 and step 1435.

[0364] Step 1431, transfer the patient. Transferring the patient refers to the process of transferring the patient from the operating room to the recovery area after the surgical procedure is completed. In some embodiments, transferring the patient can be performed by a healthcare professional with the assistance of an intelligent robot nurse.

[0365] Step 1433, 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 can control the intelligent robot nurse to perform operating room cleaning.

[0366] Step 1435, generate a surgical report.

[0367] The surgical report may include surgical related information, patient related records, participant related records, etc. In some embodiments, the processing device 210 may generate an initial surgical report based on data collected during the surgical process (e.g., sensory information collected by one or more sensory devices in the operating room). The processing device 210 may generate a surgical report based on the initial surgical report and the feedback information input by the doctor on the initial surgical report.

[0368] In some embodiments, the processing device 210 may also monitor the patient's postoperative vital signs through a vital sign monitoring device in the ward (e.g., an electrocardiogram monitor, a blood pressure monitor, etc.) to determine whether the patient's postoperative vital signs are within a normal range, whether there are any abnormalities, or whether the recovery progress is normal. In addition, the processing device 210 may update the medical advice report based on the patient's postoperative vital signs. In some embodiments, the processing device 210 may update the medical advice report based on the doctor's instructions. In some embodiments, the processing device 210 may send the updated medical advice report to a display device of a nurse workstation and / or a display device of a doctor workstation.

[0369] In some embodiments, the processing device 210 can determine a postoperative care plan based on the updated medical advice report. The postoperative care plan refers to the nursing tasks that need to be performed by nursing staff (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 for the patient according to the postoperative care plan. In some embodiments, the processing device 210 can send the postoperative care plan to the nurse so that the nurse can provide postoperative care for 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 nursing process. The execution of the postoperative care plan is similar to Fig.12 The daily plan described in .

[0370] In some embodiments, the processing device 210 can generate the doctor's surgical results and surgical records based on the surgical report and medical advice report so that the doctor can view the surgical process. The surgical results refer to data reflecting the results of the surgical process. In some embodiments, the surgical results also include the summary data of the doctor's surgical results within a predetermined time period (for example, one month). The surgical record refers to the doctor's operation record during the operation. The operation record may include action records, force records, position records, etc. In some embodiments, the processing device 210 can generate the surgical results and surgical records based on the surgical report and medical advice report.

[0371] In some embodiments, the surgical procedure is reviewed. For example, the processing device 210 can present the doctor's surgical results and operation records to the doctor, thereby allowing the doctor to review the surgical procedure.

[0372] In some embodiments, the processing device 210 (eg, an agent configured on the processing device 210) may call a data processing unit in the data processing layer 330 to perform data processing in order to implement or support at least part of the operations in the processes 900A-1400 described above.

[0373] It should be noted that the above description of the relevant processes is only for example and illustration, and does not limit the scope of application of the present disclosure. For those skilled in the art, various modifications and changes can be made to the process under the guidance of this specification.

[0374] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0375] At the same time, this specification uses specific words to describe the embodiments of this specification. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of this specification can be appropriately combined.

[0376] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this specification, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0377] Similarly, it should be noted that in order to simplify the description disclosed in this specification and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this specification, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the subject matter of this specification are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

[0378] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of this specification are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0379] Each patent, patent application, patent application publication, and other materials, such as articles, books, specifications, publications, documents, etc., cited in this specification are hereby incorporated by reference in their entirety. Except for application history documents that are inconsistent with or conflicting with the contents of this specification, documents that limit the broadest scope of the claims of this specification (currently or later attached to this specification) are also excluded. It should be noted that if the descriptions, definitions, and / or use of terms in the materials attached to this specification are inconsistent or conflicting with the contents described in this specification, the descriptions, definitions, and / or use of terms in this specification shall prevail.

[0380] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A hospital support platform, characterized in that: include: Hardware equipment, configured to collect data related to hospital operations; A data center, including a data lake, wherein the data lake is configured to persistently store the data in a tamper-proof manner; A processing device configured with a data processing unit for data processing, wherein the data processing unit includes an extended reality unit, an artificial intelligence unit, a digital twin unit, and a data circulation unit; The user space application is configured to provide users related to hospital business with user services related to the hospital business, wherein the user services are implemented by the processing device utilizing at least one of the data processing units to process at least a portion of the data stored in the data center.

2. The hospital support platform according to claim 1, characterized in that: Also includes: The software and hardware interface is configured to obtain the data from the hardware device and send the data to the data center for storage.

3. The hospital support platform according to claim 2, characterized in that: The acquiring the data from the hardware device and sending the data to the data center for storage includes: Acquire hardware configuration information of the hardware device, wherein the hardware configuration information includes a unique identity identifier; Determining whether the hardware configuration information meets a preset condition; In response to the hardware configuration information satisfying the preset condition, the data is sent to a data center for storage.

4. The hospital support platform according to claim 3, characterized in that: The hardware configuration information also includes the operating status of the hardware device; Determining whether the hardware configuration information meets a preset condition includes: Based on the unique identity identifier, determining whether the hardware device is one of a plurality of trusted devices; and / or Based on the operating status of the hardware device, determine whether the hardware device is in a normal state.

5. The hospital support platform according to claim 1, characterized in that: Also includes: The open interface is configured to allow application developers to call at least a part of the data processing unit and use the at least a part of the data processing unit to develop applications.

6. The hospital support platform according to claim 1, characterized in that: The hardware devices include Internet of Things devices and extended reality devices.

7. The hospital support platform according to claim 1, characterized in that: The data center further includes a data warehouse configured to store an index of the data.

8. The hospital support platform according to claim 1, characterized in that: The processing device is further configured to: determining evaluation information of the data; Based on the evaluation information, determining a storage strategy for the data; Based on the storage policy, the data is stored in the data lake.

9. The hospital support platform according to claim 8, characterized in that: The evaluation information includes a combination of one or more of the security level of the data, the data volume and / or the data collection frequency, and the importance coefficient; Determining the storage strategy of the data based on the evaluation information includes: In response to the security level corresponding to the data being higher than a preset security threshold, determining that the storage strategy for the data is to encrypt and store the data; and / or In response to the data volume and / or the data collection frequency being higher than a preset threshold, determining that the storage strategy for the data is to perform distributed storage on the data; and / or Based on the importance coefficient of the data, a storage period of the data is determined.

10. The hospital support platform according to claim 1, characterized in that: The extended reality unit is configured to process the data using extended reality technology to implement an extended reality service; The artificial intelligence unit is configured to process the data using artificial intelligence technology to implement artificial intelligence services; The digital twin unit is configured to process the data using digital twin technology to implement digital twin services; The data circulation unit is configured to process the data using data circulation technology to implement data circulation service.

11. The hospital support platform according to claim 10, characterized in that: At least a portion of the digital twin units are configured to call the extended reality unit and / or the artificial intelligence unit to process the data to implement the digital twin service.

12. The hospital support platform according to claim 10, characterized in that: The data circulation technology includes blockchain technology and data privacy computing technology.

13. The hospital support platform according to claim 1, characterized in that: The processing device is further configured to map at least a portion of the data to a virtual hospital using at least a portion of the extended reality unit, the artificial intelligence unit, and the digital twin unit; The user space application is configured to allow the relevant user to interact with the virtual hospital, so that the relevant user obtains at least a part of the user service.

14. The hospital support platform according to claim 13, characterized in that: The processing device is further configured to: When the relevant user interacts with the virtual hospital, at least a part of the virtual hospital is presented to the relevant user by the extended reality unit using extended reality technology.

15. The hospital support platform according to claim 1, characterized in that: The data interaction in the hospital support platform meets the preset data privacy rules and data security rules.

16. The hospital support platform according to claim 1, characterized in that: The artificial intelligence unit includes an agent unit, which is configured to maintain an agent that realizes autonomous learning and evolution based on AI technology and data related to the hospital business.

17. The hospital support platform according to claim 16, characterized in that: The agent includes a pre-consultation agent corresponding to the pre-consultation service, and the pre-consultation agent is configured as follows: Based on the department of the doctor with whom the patient is registered, conducting a pre-diagnosis inquiry on the patient through the patient terminal of the patient; The pre-consultation record is generated based on the data collected by the patient terminal in the pre-consultation inquiry.

18. The hospital support platform according to claim 17, characterized in that: The pre-diagnosis inquiry is conducted based on the inquiry content and includes multiple rounds of inquiry, wherein the inquiry content includes the inquiry content of each round of inquiry, and initiating the pre-diagnosis inquiry to the patient includes: For each round of pre-diagnosis questions except the first round, Determining semantic information and emotional information of the patient's historical answers based on data collected before the current round of questioning; Adjusting the inquiry content of the current round of inquiry based on the semantic information and the emotional information; Based on the adjusted inquiry content of the current round of inquiry, the current round of inquiry is performed through the patient terminal.

19. The hospital support platform according to claim 17, characterized in that: The pre-inquiry includes multiple rounds of inquiries, and the pre-inquiry of the patient includes: For each current round of queries except the first round of queries, Based on the inquiry content of historical inquiries, the patient's historical answers and the known information of the patient, the inquiry content corresponding to the current round of inquiries is determined using an inquiry content determination model, wherein the inquiry content determination model is a trained machine learning model; Based on the inquiry content corresponding to the current round of inquiry, the current round of inquiry is performed through the patient terminal.

20. The hospital support platform according to claim 16, characterized in that: The agent includes a medical consultation agent corresponding to the medical consultation service, and the medical consultation agent is configured as follows: During the patient consultation process, Determining whether the patient needs to communicate with the remote accompanying person based on the sensing information collected by the sensing device during the consultation process; In response to determining that the patient needs to communicate with the remote accompanying doctor, at least one terminal device is controlled to enlarge the interface element related to the remote accompanying doctor service.

21. The hospital support platform according to claim 16, characterized in that: The intelligent agent includes an inpatient intelligent agent corresponding to the inpatient service, and the inpatient intelligent agent is configured as follows: Based on the sensing information collected by the sensing devices in the ward, determine whether the patient meets the conditions for admission examination in the ward; In response to determining that the patient meets the conditions for admission examination, controlling the smart nursing cart to guide a nurse into the ward, and controlling the smart nursing cart to present information related to the admission examination; An admission record is generated based on the physical examination data of the patient collected during the admission examination.

22. The hospital support platform according to claim 16, characterized in that: The intelligent agent includes an inpatient intelligent agent corresponding to the inpatient service, and the inpatient intelligent agent is configured as follows: For each day the patient is hospitalized, Determine a daily plan for the patient based on the patient data of the patient and the doctor's instructions to the patient, wherein the daily plan includes at least one medical operation to be performed on the patient on that day; Presenting the daily plan to the patient via a terminal device in the patient's ward; and The daily plan is displayed to the nurse corresponding to the patient through the terminal device of the nurse.

23. The hospital support platform according to claim 16, characterized in that: The intelligent agent includes a surgical intelligent agent corresponding to the surgical service, and the surgical intelligent agent is configured as follows: Determine the planned route from the patient's current location to the operating room waiting area; Controlling the intelligent wheelchair to transport the patient to the waiting area along the planned route; During the process of the patient being transported to the waiting area, providing preoperative education to the patient through the patient terminal of the patient based on the patient data and the surgical plan of the patient; as well as After the patient is transported to the waiting area, the patient's identity is verified based on the patient's biological information collected by the sensing device in the waiting area.

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