71 results about "Patient status" patented technology

The invention discloses an intelligent monitoring system for tumor nursing. The intelligent monitoring system comprises a wearable sensing terminal group, a patient terminal, a cloud platform intelligent analysis center and a medical care terminal. The wearable terminal is used for collecting multi-modal physiological and behavior data such as electroencephalogram, near-infrared brain blood oxygen, heart rate variability, body movement, electrodermal response and gaits; the patient terminal is used for recording subjective symptoms and completing cognition and exercise task evaluation. The cloud platform intelligent analysis center constructs a multi-parameter individualized baseline through data fusion, noise suppression and time alignment, comprehensively analyzes real-time deviation, electroencephalogram abnormality, cognitive deviation and gait change by using a short-term acute early warning model and a long-term trend early warning model, and generates a risk level. The digital twinborn visualization module is used for dynamically displaying the state of the patient, and the medical care terminal performs clinical response based on the graded alarm board. According to the invention, extra-hospital multi-mode continuous monitoring, individualized trend identification and intelligent early warning can be realized, and the real-time performance of follow-up management of brain tumor patients is improved.

The invention discloses a visual asynchronous event triggering and calling method based on a medical information system, which comprises the following steps of: asynchronously acquiring multi-source data streams such as clinical events, equipment monitoring, doctor advice execution and patient states in the medical information system to form a multi-source asynchronous medical data stream set; generating a system event triggering association group based on the set and creating an asynchronous event scheduling strategy table; performing system event association degree calculation on the data stream to obtain a multi-dimensional asynchronous event association matrix; and carrying out system asynchronous time delay compensation and event chain visualization processing on the incidence matrix based on the scheduling strategy table, and finally generating a dynamic asynchronous event correlation topological graph. According to the invention, by constructing a system event detection operator set, establishing cross-flow system relevance calculation and establishing a priority-based asynchronous scheduling optimization mechanism, intelligent triggering, calling and early warning functions of medical system events are realized.

Systems, methods, and computer-readable media for providing a decision support solution to medical professionals to optimize medical care through data monitoring and feedback treatment are provided herein. In another embodiment, a computer-implemented method for modeling patient outcomes resulting from treatment in a specific medical area includes receiving patient-specific data associated with a patient, determining a plurality of possible patient states under which the patient can be categorized, a current patient state under which the patient can be categorized and determining probabilities of the patient transitioning from any of the possible patient states to every other possible patient state.

The invention discloses a multi-source information warning and reminding system and method for a smart ward, and the system comprises a data collection and processing module, a data fusion and analysis module, a data warning and reminding module, a warning data storage module, and a user interaction module. The data fusion and analysis module is connected with the data collection and processing module and the data warning and reminding module, and the warning data storage module and the user interaction module are both connected with the data warning and reminding module. By integrating the Internet of Things equipment and the hospital information system, the state of a patient is comprehensively perceived, the data fusion and intelligent analysis technology is utilized to carry out accurate risk study and judgment, efficient warning is realized through a collaborative distribution mechanism, the system is continuously self-optimized according to processing feedback of medical staff, and the medical staff can carry out medical care on the patient. An intelligent clinical decision support closed loop is constructed, conversion from passive response to active early warning is realized, and the method has the characteristics of comprehensiveness, accuracy and high efficiency.

An alarm notification system can enable a clinician to respond to an alarm notification received via a computing device, which may have more advanced functionality than a pager. The clinician's device can include a notification client which can respond to alarm notifications. The notification client can also provide one or more user interfaces that enable the clinician to view information about an alarm, such as information about a patient's status, physiological parameter values, trend data, audio / video of the patient, combinations of the same, or the like. Further, the notification client can provide functionality for a clinician to respond to an alarm, annotate an alarm, and / or indicate that the clinician can or cannot respond to the alarm, among other features. In addition, the clinician device can also (or instead) include an admit module that provides for automatic association of a patient to a device or location.

The invention relates to the technical field of data processing, and particularly provides a hospital guide method, system and device based on multi-modal data and a storage medium, and the method comprises the steps: obtaining the multi-modal data which is provided by a patient and comprises texts, medical images and physiological signals; extracting each modal feature vector and fusing the modal feature vectors into a unified patient state characterization vector; on the basis, confidence distribution of the target department is calculated through a probabilistic reasoning model; if the result does not reach the termination condition, iteratively executing the following core steps: calculating the information gain of each potential action in the predefined action set, obtaining new data according to the optimal action, updating the state of the patient and recalculating the confidence coefficient; and finally, outputting a hospital guide result meeting a termination condition. According to the invention, through multi-modal fusion and dynamic interaction decision making, the accuracy and efficiency of intelligent hospital guide are effectively improved.

The application discloses a kind of based on brain-computer interface and digital twinning acupuncture remote diagnosis and treatment system and method, it is related to wisdom medical field.Therein, doctor side brain-computer interface module is parsed into operation instruction vector by the movement imagination decoding model with the movement intention signal of doctor;Patient side brain-computer interface module is parsed into patient state vector by the feeling coding decoding model with the feeling intention signal of patient;Digital twinning interaction unit is used to construct and update digital twinning body, operation instruction vector is mapped to digital twinning body to generate expected qi reaction, patient state vector is mapped to digital twinning body to update actual qi state, and the difference of two is calculated to generate closed-loop control instruction;Execution unit is used to receive closed-loop control instruction to drive acupuncture execution device to carry out acupuncture operation.The application can quantitatively transfer qi feeling, realize doctor-patient two-way thought interaction fusion and have closed-loop self-adapting control ability, improve the precision, safety and doctor-patient collaboration of remote acupuncture.

Methods and apparatus disclosed herein relate to graphical representation of change in patient state. In various embodiments, one or more measured physiological parameters of a patient may be analyzed, which includes determining a rate of change in one or more of the measured physiological parameters over time. Based on the analysis, a graphical user interface (GUI) may be rendered. The graphical user interface may include a comet-shaped graphical element that conveys the rate of change in the one or more of the physiological parameters over time. For example, the comet-shaped graphical element may include a tail that is sized or shaped to convey the direction and the rate of change.

Systems and techniques can be used to estimate patient state during radiotherapy treatment. For example, a method can include generating, with a preliminary motion model, an extended dictionary of potential patient measurements and corresponding potential patient states. The method can include training, with a machine learning technique, a correspondence motion model that associates input patient measurements with output patient states using the dictionary. The method can include estimating, with a processor, a patient state corresponding to an input image using the correspondence motion model.

1. The name of the design product: computer with refractive ophthalmic procedure service graphical user interface. 2. The use of the design product: for running programs, touch interaction and displaying information. 3. The design points of the design product: the content displayed on the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 front view. 5. The computer is an existing design, omit rear view, left view, right view, top view, bottom view. 6. Design 1 is designated as the basic design. 7. The use of the graphical user interface: for the management of patient status records and data in ophthalmic refractive surgery procedures. The human-computer interaction mode of the graphical user interface: click "message" in design 1 front view to enter design 1 interface change state diagram 1; click the first "XXX" in supplementary interface 1 to enter design 1 interface change state diagram 2, click the lower "lens file" in supplementary interface 2 to enter design 1 interface change state diagram 3; click "message" in design 2 front view to enter design 2 interface change state diagram 1; click the first "XXX" in supplementary interface 1 to enter design 2 interface change state diagram 2, click the lower "lens order" in design 2 interface change state diagram 2 to enter design 2 interface change state diagram 3.

The invention discloses an intelligent pressure sore prevention nursing pad and a control method thereof, and belongs to the technical field of medical instruments, and the intelligent pressure sore prevention nursing pad comprises a support formed by splicing a plurality of supporting parts and a contact part covering the upper end of the supporting part; wherein any supporting part comprises a first supporting piece and a second supporting piece, the first supporting piece comprises a first support, the second supporting piece comprises a second support, and the first support and the second support are alternately placed on the lower side of the contact part; the first support is fixedly connected with a first lifting device. The second support is fixedly connected with a second lifting device. The detection device is used for detecting the state of the patient according to the input electric signal; the execution device is used for controlling the first supporting piece and / or the second supporting piece according to the received electric signal; and the control device is used for sending a control signal to the execution device according to the control signal sent by the detection so as to control the movement of the first supporting piece and / or the second supporting piece.

The invention relates to the technical field of first-aid medical informatization, in particular to a first-aid transfer path intelligent recommendation method and system based on the AI technology, and the method comprises the following steps: S1, collecting vital sign data of a patient, vehicle running state data and traffic road condition data, carrying out cleaning and space-time alignment, and constructing a first-aid transfer state data set; and S2, performing illness criticality assessment and hospital resource matching based on the first-aid transfer state data set, locking a target hospital through a two-way resource interaction protocol, and generating a main navigation path. According to the method, the vital signs of the patient, the running state of the vehicle and the real-time road condition data are subjected to unified space-time alignment, and illness criticality evaluation, hospital resource locking and track re-planning based on medical operation stability are introduced, so that the first-aid transfer path can be dynamically adjusted according to the state of the patient and the road condition; therefore, the medical continuity and the path decision accuracy of the critical patient in the transfer process are remarkably improved, and the overall treatment efficiency is improved.

The invention relates to the technical field of medical equipment systems, in particular to a method for realizing patient priority operation in an intelligent outpatient service scene, which comprises the following steps of: 1, advancing a patient in a preliminary diagnosis state; according to the method for realizing the patient priority operation in the intelligent outpatient service scene, queuing sequence optimization: through configuration setting, several serial numbers are reserved in advance and are not participated in generation, so that the queuing sequence can be effectively optimized, and the situation that re-visit patients or number-missing patients are ranked behind more preliminary visit patients is avoided; therefore, the problem that the doctor cannot see the doctor in time within the working time is solved. According to the method, after the method is inserted into a specified patient through manual operation, a related serial number is modified into a form of'a patient state + a maximum sorting number of a patient in a current state plus one ', so that the waiting time of the patient with the number missing can be effectively shortened, and dissatisfaction brought to the patient is reduced.

This invention relates to the field of data analysis technology, specifically disclosing a method and system for secure sharing and exchange of ICU data. The method and system are characterized by the following steps: Patient status data is input into a pre-built clinical pathway prediction model to generate predicted pathway data; based on key department identifiers in the predicted pathway data, a pre-authorization token is generated for each key department identifier, and the generated pre-authorization token is sent to the corresponding department's server; according to the pre-authorized data range identifier, matching target patient data is filtered from the patient status data, and the target patient data is pre-fetched to the edge cache node corresponding to the department server; access intent data is extracted from data access requests; it is determined whether there is a target pre-authorization token that matches the department identifier and is in a valid state; and it is determined whether the data type identifier of the requested access falls within the pre-authorized data range identifier associated with the target pre-authorization token. The advantage is that it improves the efficiency of secure data sharing and exchange.

This application discloses a medical data processing method based on generative AI, belonging to the field of medical data processing technology. The method includes: performing AI question-and-answer sessions with patients and receiving feedback text; obtaining standard symptom vectors based on mapping functions; calculating the cosine similarity with each vector in a standard entity library to determine fuzzy text; extracting speech emotion features to obtain input vectors; reconstructing the current state vector and uncertainty vector based on latent variables; identifying the patient's communication intent; and constructing a continuous quantization mapping mechanism to transform the patient's inexpressible vague feelings into a high-dimensional state vector sequence, overcoming the shortcomings of existing technologies in capturing patients' fuzzy information and implicit states, and achieving refined quantitative perception of the patient's condition. By decoupling the patient's state vector, which contains multiple factors, into independent factors with clear clinical semantics, the method clearly distinguishes the dominant factors leading to changes in the condition, solves the problem of causal attribution of changes in the condition, and improves the value of follow-up visits.

A model-assisted system for extracting patient information. The processor may be programmed to access a database storing one or more medical records associated with a patient and to use a first machine learning model to determine whether the patient is associated with a condition based on unstructured information included in the one or more medical records. The processor may be further programmed to identify a date associated with the patient and to use a second machine learning model to determine whether the patient is associated with the condition associated with the date based on the unstructured information. The processor may generate an output indicating whether the patient is associated with the condition and whether the patient is associated with the condition associated with the date.

The application discloses an ambulance route planning method based on patient state, and relates to the technical field of route planning. The method comprises the following steps: acquiring vital sign data of a target patient and a departure position of the target patient; determining whether the target patient is infected with a virus according to the vital sign data; if the target patient is infected with the virus, acquiring human flow density data and path environment data between the departure position and a target position of an ambulance; and planning a route of the ambulance according to the human flow density data and the path environment data. The application can avoid the areas with concentrated human flow and the areas where the virus is easy to spread, so as to avoid the transmission path and the infection receptor, thereby reducing the infection of bacteria in the first-aid route.

1. The name of the design product: status display part of a status monitoring graphical user interface for an electronic device. 2. The use of the design product: an electronic device. 3. The design points of the design product: the content shown by solid lines in the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 front view. 5. Design 2 is designated as the base design. 6. The use of the graphical user interface: for visualizing status, such as monitoring diabetes management status, blood glucose status, blood glucose trend, risk status, patient status, and prediction status. 7. The human-computer interaction mode of the graphical user interface: the user can obtain status information from the interface; for example, the user can obtain information related to diabetes management status, blood glucose status, blood glucose trend, risk status, patient status, or prediction status by observing the interface. 8. Other circumstances that need to be explained: the claimed design design 1, design 3, design 5 contains color. The present design is a partial design, wherein the part shown by the dashed line is not claimed. The outer boundary shown by the dashed line in the view represents a display screen or part of a display screen, which is part of an electronic device (such as a computer or a mobile phone) with a display screen.

In a procedure for determining a multimodal (patient) conditiona current (patient) state consisting of data from at least two unimodal state indicators Xk with k=1; . . . ; n and n≥2 is measured or calculated;there is a historical (population) data set with data from at least two state indicators Xk and at least one reference indicator X0;there is a correlation between the at least two state indicators on the one hand and the at least one reference indicator on the other;the at least two state indicators Xk and the at least one reference indicator X0 span an orthogonal state space;regression functions are calculated in the state space with the historical (population) data set, which contain at least one reference indicator X0 as an independent variable;and for a current (patient) state, at least one current, n-modal (n≥2) expectation value μnM of the currently unknown reference value is calculated on at least one reference axis X0 of the state space using the regression functions.

This invention provides a postoperative data analysis and summarization system for obstetrics and gynecology, comprising: a data acquisition module for real-time acquisition of multi-source heterogeneous data from postoperative obstetrics and gynecology patients, wherein the multi-source heterogeneous data includes vital sign time-series data, biochemical test data, and electronic medical record text data; this invention constructs a hybrid feature matrix containing vital sign time-series features, biochemical indicator discrete features, and text semantic features, establishes a postoperative complication risk prediction model using an improved weighted random forest algorithm, and introduces the principle of information entropy reduction to summarize and reduce the dimensionality of massive postoperative data, thereby solving the problems of low utilization rate of postoperative obstetrics and gynecology data, delayed risk warning, and difficulty in summarizing unstructured data in existing technologies, realizing real-time monitoring and accurate assessment of postoperative patient status, and possessing significant novelty and inventiveness.

A medical device and an information display method are disclosed. The medical device includes a memory for storing an executable program, a processor and a display. The processor is used for executing the executable program to perform following operations: acquiring patient data of a patient, which includes monitoring data of one or more vital sign parameters of the patient; analyzing the patient data according to preset rules to obtain the patient state of the patient and a comparison result of at least one vital sign parameter associated with the patient state and a preset alarm condition; and presenting in the display the patient state on a human body diagram, and via text or graphics, the comparison result of the at least one vital sign parameter associated with the patient state and the preset alarm condition.

The invention discloses a fixing device for mental patient treatment, and relates to the technical field of medical instruments.The top of a base is provided with a main bed board, the top ends of the two sides of the base are hinged to auxiliary bed boards, a folding control module is arranged on the base and is in transmission connection with the two auxiliary bed boards, and a binding mechanism is arranged on the main bed board; the main controller is fixedly arranged on the base, an alarm is integrated on the main controller, a displacement module is arranged on one auxiliary bed board, the output end of the displacement module is connected with a helmet, and a detection module is arranged on the helmet and used for detecting the mental state of the mental patient. According to the nursing bed, the foldable bed body is adopted, when the bed body is used, the bed body can be transformed into a chair firstly, a nurse can fix a patient on the bed body conveniently, then the bed body deforms to drive the patient to lie down, meanwhile, the arranged alarm mechanism can monitor the mental state of the patient in real time, and the nurse is reminded when the state of the patient is poor; and the labor intensity of nursing personnel can be reduced.

The present disclosure includes a host device that is part of a patient monitoring system. The host device can provide an improved, organized, uncluttered, and graphically-rich display that presents an integrated display of real-time patient data and alarms from multiple integrated or non-integrated devices, such as patient monitors, ventilators, anesthesia gas machines, or intravenous (IV) pumps. The host device may provide a supplementary display for the patient data collected by the multiple devices and present information, such as comprehensive real-time patient status, historical trends, or alarm indicators, in an organized manner for particular clinical scenarios. The one or more displays can be central to a care team for a patient, and the care team can together simultaneously view and act upon the information presented.

Disclosed herein is a computer implemented method for managing healthcare diagnosis and treatment. The method includes the steps of monitoring at least one data source for a workflow trigger comprising at least one of an order, a test result, an appointment, a patient demographic, a patient status, a patient history, a patient communication, or a condition; and triggering a workflow upon the detection of a workflow trigger. The workflow comprises a first decision-making layer configured to manage at least one of a rule, a patient test, and a patient communication; a second decision-making layer configured to manage at least one workflow, wherein the workflow comprises at least one rule; and a third decision-making layer configured to manage at least one machine learning model, wherein the machine learning model is configured to process data relevant to the workflow and to determine a probability of a condition to be tested.

In one example, a sensor system of a patient monitoring system includes a voiding sensor that includes an electrical circuit configured to be transitioned from a first impedance state to a second impedance state in response to a voiding event in an absorbent region of an absorbent article worn by a patient. The sensor system also includes one or more processors configured to:determine, based on whether the impedance state of the electrical circuit is open or closed, that the voiding event has occurred; and generate, based at least in part on the occurrence of the voiding event, patient status data of the patient. The sensor system also includes a communication module configured to wirelessly transmit, via a relay module, the patient status data to a remote monitoring device that is distinct from the relay module.

To recommend the most suitable treatment from a large number of options, in line with the patient's wishes, without placing a burden on the patient. [Solution] The medical information processing device of the embodiment comprises a patient state estimation unit and an evaluation unit. The patient state estimation unit receives at least the patient's first state and treatment candidates as input, and estimates and outputs a second state of the patient that occurs after the transition from the first state to the patient by adapting the treatment candidate to the patient. The evaluation unit inputs a plurality of different treatment candidates to the patient state estimation unit, and calculates an evaluation value for each of the plurality of treatment candidates based on the plurality of second states output and the tolerance for parameters related to the loss the patient will suffer as a result of the treatment.

The present application relates to the technical field of medical Internet of Things, and in particular to a self-adaptive infusion collaborative control method and system based on intelligent decision-making. The method comprises: an end device analyzes multi-modal physiological time series data and infusion parameters through an end-to-end patient state evaluation model integrated in a sub-body infusion unit, and outputs a patient state index and infusion suggestions; combined with a pipeline pressure signal, an adaptive flow rate control algorithm based on LSTM is used to generate motor control instructions to realize closed-loop control. The edge device periodically aggregates local model parameter updates of multiple end devices through a mother base station. The cloud device fuses all updates uploaded by the edge devices based on a federated averaging algorithm, generates an optimized global model, and issues the global model. The present application realizes a paradigm shift from isolated execution to collaborative perception-decision-evolution of infusion, drives continuous evolution of group intelligence under the premise of protecting data privacy, and improves the accuracy, safety and overall intelligent level of infusion therapy in complex environments.

The application provides an intelligent scheduling method and system for a multi-mode emergency treatment process, and relates to the technical field of medical resource scheduling. Firstly, the application collects real-time vital sign data and illness description data of emergency patients to form a multi-dimensional patient data set. Secondly, the application evaluates the emergency level and the required treatment mode type and obtains the medical resource state data of the emergency department. Thirdly, the application generates a multi-mode process scheduling instruction in combination with the emergency level, the required treatment mode type and the medical resource state data. Finally, the application executes the treatment process according to the multi-mode process scheduling instruction and continuously monitors the patient state and resource changes during the execution of the treatment process to update the multi-mode process scheduling instruction. The technical scheme provided by the application realizes standardized grading and dynamic scheduling planning by fusing multi-dimensional patient and resource data, and improves the response efficiency, resource utilization rate and process robustness of emergency treatment through closed-loop adaptive optimization.

Abstract Systems and methods disclosed offer improved heart failure patient outcomes by automatedly extracting features from vessel area traces and generating cardiac health indicative parameters based on extracted features to provide a normalized congestion index to assess patient status. Examples include diagnostic engine (102) receiving area traces from trace generator (104) and communicating patient status information through user interfaces (116). The diagnostic engine may comprise trace feature detector (106), metrics generator (108), boundary generator (110), index generator (112) and decision logic (114). Disclosed systems may be executed using one or more processing devices or in a networked, distributed processing system. Abstract 20 26 21 40 90 07 A ug 2 02 6 A b s t r a c t 2 0 2 6 2 1 4 0 9 0 0 7 A u g 2 0 2 6

A risk-based patient monitoring system for critical care patients combines data from multiple sources to assess the current and the future risks to the patient, thereby enabling providers to review a current patient risk profile and to continuously track a clinical trajectory. A physiology observer module in the system utilizes multiple measurements to estimate Probability Density Functions (PDF) of a number of Internal State Variables (ISVs) that describe components of the physiology relevant to the patient treatment and condition. A clinical trajectory interpreter module in the system utilizes the estimated PDFs of ISVs to identify under which probable patient states the patient can be currently categorized and assign a probability value that the patient will be in each of the identified states. The combination of patient states and their probabilities is defined as the clinical risk to the patient.