511 results about "Health information" patented technology

The invention discloses a multi-agent collaborative decision-making system and method based on knowledge Token, and the method comprises the following steps: S1, constructing a knowledge base architecture, executing the content Hash calculation, and generating an original fingerprint in an original fidelity layer; s2, extracting content, packaging the content into knowledge Token, and writing identification, semantics, source, authority, value, contract, association, traceability and health information; s3, activating a knowledge layer, constructing a vector index and mapping knowledge graph nodes; s4, unifying an index layer, matching task requirements, and screening and verifying candidate Tokens to obtain an authorization set; s5, the multiple agents generate local decisions and fuse values and semantics to form a collaborative result; and S6, binding a Token identifier after consistency verification, generating a collaborative decision and recording data consanguinity information. According to the method, multi-agent collaborative decision-making is realized through the knowledge Token and the knowledge graph, and the decision-making accuracy and traceability are improved.

The invention relates to the technical field of old people health management, and discloses a personalized health auxiliary management system based on artificial intelligence, which comprises a multi-mode sensing module, an intelligent preprocessing module, a dynamic knowledge graph module, a personalized inference engine module and a self-adaptive communication and interaction module. The multi-mode sensing module is used for acquiring physiological, environmental and behavioral data; the intelligent preprocessing module desensitizes and cleans data through federal learning, and extracts core features; the dynamic knowledge graph module constructs and updates an exclusive graph containing basic and dynamic nodes and associated edges; the personalized inference engine module generates a layered intervention scheme; and the adaptive interaction module adapts to the cognitive ability and synchronizes the scheme. According to the invention, health information integration and dynamic intervention are realized, the management accuracy and compliance are improved, and the method is suitable for home non-clinical scenes.

The invention relates to a personalized traditional Chinese medicine health-care intelligent recommendation system combined with an acupuncture theory. The system comprises a multi-modal data acquisition module, an AI diagnosis module and an acupuncture scheme generation module. According to the invention, the health information of the user is acquired through the multi-modal data acquisition module, the deep learning model fused with the acupuncture meridian theory is utilized to realize physique identification and disease diagnosis, and the personalized acupuncture health care scheme is generated based on the established acupuncture point, physique and disease three-dimensional association database. A reinforcement learning algorithm is combined with a user real-time feedback dynamic optimization scheme, the limitation that traditional acupuncture depends on physician experience is broken through, intelligentization, individuation and dynamics of acupuncture health care are achieved, the accuracy and operability of the health care scheme are improved, and the method is suitable for various scenes such as family health care and community medical treatment and has a wide application prospect. The method has remarkable innovativeness and practicability, the physique and the disease of the user are accurately identified based on multi-modal data, the acupuncture scheme adaptive to personal characteristics is generated, and the problem that a traditional universal scheme is insufficient in adaptability is solved.

The invention relates to a recording method and system of an electronic medical record, and aims to comprehensively and systematically collect health information of a patient through diversified input terminals, improve information input efficiency, ensure information integrity and promote team cooperation. The system comprises a medical professional terminal, a patient direct related terminal and other patient related terminals, supports information input in various forms of pictures, characters, videos, audios and the like, and covers various input devices such as portable devices, professional examination instruments and the like. And the information storage module ensures accurate homing of the data and supports cross-mechanism data integration and sharing. The system also has the functions of electronic medical record automatic generation, treatment tracking, symptom and sign extraction, intelligent analysis and early warning and the like, provides efficient and accurate information support for medical services, optimizes medical resource configuration, and enhances medical experience of patients. The method is suitable for modern medical management, and particularly has remarkable advantages in the aspect of improving the intelligence and integration level of an electronic medical record system.

The present invention concerns a computer-implemented method (300) for enriching ambiguous, incomplete or sparse health data, comprising: obtaining an input dataset (302) comprising a plurality of electronic health records (EHRs) associated with a patient; extracting (308) health information which is explicitly recited in the EHRs from the input dataset (302), including at least one diagnosis indicated by a name of a disease (504) or a medical classification code (502) which denotes a disease (504); generating (310) supplementary health information which is not explicitly documented in the EHRs based, at least in part, on the extracted health information, the supplementary health information including at least one or more symptoms (506) inferred from diseases (504) directly or indirectly documented in the input dataset (302); and validity-scoring (312) at least part of the extracted health information and the supplementary health information to produce an output dataset (314).

The invention discloses a traditional Chinese medicine five-tone treatment personalized music generation system based on a large language model and a construction method thereof. The invention designs a double-layer architecture technical route of firstly performing traditional Chinese medicine syndrome differentiation decision and then generating five-tone music. Meanwhile, according to the characteristics of traditional Chinese medicine syndrome differentiation treatment individuation and five-tone therapy accuracy, an intelligent syndrome differentiation engine based on a large language model and a five-tone music generation framework based on traditional music pre-training are provided, and the treatment thought of traditional Chinese medicine treatment based on syndrome differentiation and according to different persons is achieved through multi-dimensional health information fusion and a five-tone feature constraint mechanism. The technical problem of fusion of the traditional Chinese medicine theory and the modern AI technology is solved. The intelligent level and the individuation degree of the treatment scheme are remarkably improved while the theory integrity of the traditional Chinese medicine five-tone therapy is kept, and a complete technical solution is provided for modern application of traditional Chinese medicine music treatment.

Embodiments of the present disclosure provide a context based health visualization system and method for a computing environment that indicates context-based health information for the computing resources of a computing environment. According to one embodiment, an Information Handling System (IHS) includes computer-executable instructions to identify a maintenance task that needs to be performed on a computing resource, classify the maintenance task according to one of a plurality of health contexts, and generate, using information associated with the maintenance task, a health context score for the one health context. The maintenance task may be one that impacts an overall health score of the computing resource. The instructions may then cause the IHS to display the health context score for view by a user.

The invention provides a vehicle health state determination method and an unmanned vehicle, which can be applied to the technical fields of vehicle control, intelligent auxiliary driving, intelligent mines, vehicle maintenance and the like. The method comprises the steps that operation information, road surface slippery information and current health information of a target vehicle are obtained, the target vehicle comprises a vehicle executing operation in an open-air place, the current health information represents the health state of vehicle parts of the target vehicle, and the operation information is collected when the target vehicle executes operation; determining a loss increment parameter matched with the pavement slippery information; and correcting reference loss information determined based on the operation information by using the loss increment parameter, and determining the health state of the vehicle part according to the difference between the corrected reference loss information and the current health information.

The invention discloses a speaker segmentation method based on multi-scale feature fusion and voiceprint perception density clustering, and relates to the technical field of speaker segmentation. The method comprises the following steps: extracting at an extraction point of a target voice to obtain an extraction point voiceprint; selecting a reference point, and collecting a reference speaker and a reference voiceprint; if the voiceprint of the extraction point is not consistent with the reference voiceprint, judging whether multi-person talking overlapping exists or not according to the voiceprint perception density, and if the multi-person talking overlapping does not exist, judging whether the extraction point is used as a voice conversion point or not according to the health information and the environment information of the reference speaker; if yes, judging whether the extraction point is used as a voice conversion point or not according to the voice content of the extraction point and the background noise probability; and classifying the voice segments according to the voice conversion points to realize speaker segmentation. According to the invention, the resource utilization rate of speaker segmentation based on multi-scale feature fusion and voiceprint perception density clustering is improved.

The invention discloses an information processing method and device for examination item recommendation, equipment and a medium, relates to the technical field of medical data processing, is applied to a computer device and comprises the steps that key feature vectors in health information of a target object are extracted; querying an initial disease name and an initial confidence coefficient corresponding to the vector from a medical knowledge graph; according to the initial disease name and the initial confidence coefficient, generating a health state evaluation list which corresponds to individual attribute information in the health information and comprises a target disease name and a corresponding target confidence coefficient; generating a preliminary recommendation table of the target object based on the health state evaluation list, wherein the recommendation table comprises initial medical examination items sorted based on the target confidence; and optimizing the preliminary recommendation table according to the evaluation information and the individual attribute information of each initial medical examination item to obtain a target recommendation table containing the target disease name and the corresponding target medical examination item. And personalized and high-accuracy medical examination item recommendation is realized.

The invention discloses a big data analysis-based occupational health management system optimization method. The method comprises the following steps of 1, collecting and preprocessing multi-source health information data of employees; 2, mapping the multi-modal data set into a unified-dimension employee health feature tensor; 3, constructing a health risk isomerism map based on the employee health feature tensor; 4, inputting the health risk heterogeneous atlas into the improved GATv2 model to obtain a health risk embedded representation vector; 5, performing risk assessment on the health risk embedded representation vector, and identifying a high-risk employee node; step 6, constructing an intervention action candidate set for the high-risk employee nodes, and generating an optimal intervention strategy by adopting an MOPSO algorithm; and step 7, executing the optimal intervention strategy and generating a score of an intervention effect. According to the invention, the improved GATv2 model and the MOPSO algorithm are fused, and dynamic assessment and accurate intervention of occupational health are realized.

The invention discloses a mental stress assessment and intelligent dredging method and system, and belongs to the technical field of digital medical treatment and health informatics. Multi-modal physiological signals are continuously collected through the wearable device, medical diagnosis level pressure state evaluation is carried out based on the personalized physiological baseline, and personalized pressure indexes and levels are generated; secondly, when it is diagnosed that the pressure level exceeds the standard, the system serves as an intelligent decision support system, the environment and schedule information after privacy protection processing is fused, and an optimal grooming action is dynamically selected from a predefined intervention action library and executed; finally, the system serves as a continuous learning system, the intervention efficiency is evaluated in real time according to feedback data of the pressure index after execution, the decision model is updated, and collaborative self-optimization of the diagnosis strategy and the intervention strategy is achieved. According to the method, medical diagnosis, personalized treatment decision and adaptive learning are integrated, and the systematicness, accuracy and intelligent level of mental stress related health problem management are improved.

The invention relates to the technical field of health information processing, and particularly discloses a user health data intelligent acquisition and management system based on data analysis, which performs event analysis and standardized coding on original health data to generate a user-level standardized event sequence; automatically constructing a causal structure network representing the causal relationship between the event types by analyzing the time delay dependence between the event types and executing a conditional independence test; further, instantiating a specific event into a node according to the causal network and a personal event sequence, establishing an edge with tense and causal composite attributes, and constructing a personalized event association network; performing data completion and prediction through multi-hop attribute propagation and multi-path evidence aggregation based on the network, and outputting a result with confidence evaluation; and dynamically optimizing the network by using a high-confidence result, and analyzing an influence propagation path of a key event to generate a personalized health analysis conclusion.

The invention provides a method, a device and a system for providing a boxing education plan for children. In the method for providing a boxing education plan for a child, the method is executed by a device, and user information of a first student is received from a terminal of a first school supervision; confirming age information, height information, target information, health information, weakness information and exercise history information of the first student according to the user information of the first student; making a first training plan, namely a boxing training plan for the first participant according to the health information, the weakness information and the exercise history information of the first participant, the age information, the height information and the target information of the first participant; and providing a customized boxing education plan for the first participant, wherein the method comprises a step of sending a notification message for recommending the first training plan to a terminal of the first training center.

The invention belongs to the technical field of health information processing and management, and discloses a personalized health management service system based on multi-source data fusion, which comprises a data acquisition device access wearable device, a health application, a medical information system and a user terminal entry data, the fusion processing platform carries out missing completion, abnormity elimination, time alignment and weighted fusion on the data to form a weighted fusion sequence, the cross-domain correlation builder generates a correlation map of lifestyles and clinical indexes, and the risk modeling engine outputs individual health risks under the constraint of the map. The management scheme generator generates personalized diet, exercise, sleep and disease prevention schemes under the constraint of the rule base. The compliance evaluation system combines subjective feedback and objective monitoring to form scores, the scheme adjustment mechanism executes minimum disturbance update based on scores and atlas trends, and the auditing unit realizes whole-process data tracing and compliance guarantee.

Described herein are systems and methods for signal digitization. A system may include a camera; a network interface device; a user interface; and a computing device configured to, using the camera, capture an image of a signal; determine a signal metric as a function of the image of the signal; and using the user interface, display the signal metric to a user; wherein the system is communicatively connected to a repository of deidentified patient health information.

The application discloses a mental health evaluation method and system based on brain area electric stimulation, relates to the technical field of medical and health information science, and creatively integrates brain area electric stimulation into mental health evaluation. The basic cognitive level and neural plasticity potential of a measured person are objectively quantified through comprehensive scores before and after brain area electric stimulation, so that corresponding suitable mental health evaluation test questions are selected based on the basic cognitive level and neural plasticity potential, and the precision, sensitivity of corresponding mental tests and the mental comfort of the measured person are significantly improved. A decay quantization model of a stimulating current from an electrode to the brain is given, the decay quantization model is used to accurately control the electric quantity, and the maximum beneficial effect is realized under the condition of guaranteeing health and safety. Historical data accumulated in the application process can be effectively used to solve medical problems, such as the influence of brain area electric stimulation on child neural development evaluation, early warning of mental illness and brain function reinforcement.

The invention discloses a deep vein thrombosis risk early warning health information system based on dynamic negative pressure monitoring and AI, and relates to the technical field of intelligent medical health information. Comprising a dynamic negative pressure sensor module, a multi-modal data acquisition module, a waveform primitive analysis module, a hierarchical attention fusion module, a risk assessment classifier module and an early warning output module. The dynamic negative pressure sensor module is used for continuously collecting dynamic negative pressure signals of the lower limbs of the user. According to the dynamic negative pressure monitoring and AI deep vein thrombosis risk early warning health information system, the problem of multi-source heterogeneous physiological data fusion is solved; an original dynamic negative pressure signal is converted into a symbolized primitive sequence with clear physiological significance, so that the data quality is fundamentally improved; according to the method, adaptive fusion of multi-modal data and accurate focusing of key time slices are realized, the specificity and robustness of a risk assessment model are improved, and a false alarm phenomenon caused by physiological activity interference is reduced.

The invention discloses a cardiovascular risk early warning method based on multi-modal time sequence data, relates to the technical field of medical health information monitoring, and aims to solve the problem of confusion of causes of dyspnea at night by constructing a cross-modal direction and time delay relation in a sliding time window. Phenotype similar phenomena such as pure blood oxygen reduction / wake-up are decomposed into a comparable time sequence interaction structure, so that a blocking chain type process and a non-blocking type heart failure related process can be distinguished on the structural level, and therefore false alarm and missing alarm caused by confusion are reduced. Meanwhile, a multi-channel signal is firstly converted into a time sequence causal diagram, and then in-window statistical characteristics are combined for judgment, so that the model not only utilizes the self change of each channel, but also utilizes the interaction evidence of the first and second channels, the influence direction and the delay length, and the expression ability of the pathophysiological chain difference is improved.

The invention relates to the technical field of health information, in particular to a dietary inflammation tendency analysis system based on a nutrition database, which comprises a nutrition data acquisition module, a user health data acquisition module, an inflammation tendency analysis engine and a personalized diet suggestion generation module, nutrient components and user health indexes are mapped to a unified inflammation semantic space through a multi-dimensional feature embedding technology, a dietary inflammation tendency index fusing food components, metabolic states and inflammation markers is dynamically calculated based on a deep learning model, and personalized analysis is realized in combination with cloud platform data synchronization and machine learning optimization. According to the scheme, accurate quantification and dynamic evaluation of the individualized dietary inflammation risk can be realized, and the problem of insufficient analysis precision caused by data isomerism and static rules in a traditional method is solved.

Systems and methods for handling platform-agnostic pre-boot health information in an Information Handling System (IHS) are described. In an illustrative, non-limiting embodiment, an IHS may include a processor; and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: create an Advanced Configuration and Power Interface (ACPI) table, by a Basic Input / Output System (BIOS) during boot of the IHS, wherein the ACPI table comprises telemetry data and an identifier; and provide the ACPI table to an Operating System (OS) application, wherein the host OS application is configured to select one of a plurality of parsers to process the ACPI table based, at least in part, upon the identifier.

Systems and methods are disclosed herein for visualizing and managing health information data, the system comprising: one or more subsystems adapted to receive health information data of one or more patients; a display device configured to display a viewing framework; a computing system communicatively coupled to the one or more subsystems, the display device, a memory, and a processor, wherein the processor comprises program instructions that, when executed, causes the processor to perform operations comprising: receiving the health information data; determining clinical context information of the health information data to generate contextualized data; converting the contextualized data into usable data using trained machine learning models; detecting viewing parameters; determining the viewing framework based on the usable data and viewing parameters; and sending the viewing framework to the display device automatically.

A method includes obtaining, by an electronic device, one or more user data types from one or more health devices communicatively coupled to the electronic device, including, by the electronic device, the one or more user data types in a user database, receiving, by the electronic device, an input via a user interface, and generating, using large language model (LLM) agents associated with the user database, user-specific health information based on the input, one or more user data types and a user-specific healthcare data, and providing, by the electronic device, the user-specific health information via the user interface. The user-specific healthcare data may be accessed from a healthcare database communicatively coupled to one of the LLM agents.

A memory device including a memory block, a cell counter, and a health information manager. The memory block includes a plurality of select transistors connected to a plurality of select lines and a plurality of memory cells connected to a plurality of word lines. The cell counter counts a number of degraded select transistors which exceed a normal threshold voltage distribution width among the plurality of select transistors, based on a cell current of the plurality of select transistors, and generates cell count information including the number of the degraded select transistors. The health information manager generates read reclaim information indicating whether the memory block is a read reclaim target according to a remaining read count of the memory block and a result obtained by comparing the remaining read count with a plurality of threshold read counts, based on the cell count information.

The invention relates to a remote health monitoring method and device based on the Internet of Things. The method comprises the following steps: acquiring real-time physiological data and historical health information of a user; determining an individual dynamic threshold interval according to the historical health information; according to the individual dynamic threshold interval, judging whether an abnormal fluctuation data combination exists in the real-time physiological data or not to obtain a judgment result; if the judgment result is that the abnormal fluctuation data combination exists, analyzing the abnormal fluctuation data combination to obtain an analysis result, and obtaining a potential health risk assessment result according to the analysis result; and generating a corresponding health early warning output result according to the potential health risk assessment result. By adopting the method, precise remote health monitoring can be realized, and the false alarm rate and the missing report rate are effectively reduced.

The system brings together patient data both clinical records and imaging studies from disparate sources to the user workstation or mobile device in real-time and on-demand. In order to do so, the system needs to establish application layer connectivity utilizing HL7 or FHIR and DICOM for imaging. Once a secure connection is established, the system is able to search and retrieve records and present it to end user.

A method for providing access to communication network health information using a communication-network-aware generative AI RAG model includes receiving, as a first input to the RAG model, a query for communication network health information and receiving, as a second input to the RAG model, at least one feed of communication network health information regarding at least one NF. The method further includes using the query to extract, from the communication network health information regarding the at least one network function, context information for the query for communication network health information, providing the query and the context information as inputs to a base LLM component of the RAG model, and generating, as output, a query response including an indication of the communication network health information requested by the query and in a natural language format.

A system for providing healthcare information regarding a patient's hospital visit includes a health information application that operates on a plurality of electronic devices. The application displays first data regarding the patient's visit; processes information indicating a current location of the mobile electronic device; and displays second data regarding the patient's visit that is delayed until the mobile electronic device crosses a boundary of a geo-fenced area. The electronic device may also communicate with a bed server at the healthcare facility and authorize the bed server to automatically send a notification message to a second mobile electronic device associated with the patient's friend or family member based on the patient's sleep status and / or movement into or out of bed. The application may also gather and process data useful to healthcare administrators, such as HCAHPS survey scores, status data for medical devices, equipment servicing information, and other information.

The invention relates to the technical field of artificial intelligence health consultation, and discloses a remote health consultation method and system based on artificial intelligence. The method comprises the following steps: receiving a health consultation request submitted by a user through terminal equipment, wherein the request comprises basic health information of the user and a specific consultation question; the basic health information is preprocessed to generate a standardized health data record, and the problems that existing health information is not uniform in format and difficult to efficiently analyze are solved; the standardized data are input into the trained health assessment model, and comprehensive and objective analysis of the health condition of the user is completed; retrieving associated medical knowledge nodes from a medical knowledge graph according to a model analysis result, and providing a professional medical basis for a consultation scheme; and in combination with the medical knowledge node and the user consultation question, constructing a personalized health consultation scheme and sending the personalized health consultation scheme to the user terminal equipment. The method can quickly respond to the consultation demand of the user, guarantee the scientificity and pertinence of the consultation scheme, and effectively improve the remote health consultation experience.

The invention relates to the technical field of tunnel state diagnosis and early warning, and discloses a tunnel health state intelligent diagnosis and early warning method based on multi-modal fusion, which comprises the following steps of: 1, arranging various types of sensors on a tunnel structure, multi-modal data information such as vibration response, reinforced concrete corrosion condition, circumferential strain, structural temperature, longitudinal pipe joint opening displacement and water leakage, traffic load and the like is collected in real time. According to the tunnel health state intelligent diagnosis and early warning method based on multi-modal fusion, through deep fusion of sensing data of multiple modals, the advantages of different sensors are fully played, information islands among data of all modals are broken through, advanced data fusion algorithms and models are utilized, deep mining and analysis are carried out on multi-source heterogeneous data, and the tunnel health state intelligent diagnosis and early warning method based on multi-modal fusion is realized. The health information of the tunnel structure can be obtained more comprehensively and accurately, fine evaluation of the health state of the tunnel is achieved, and the reliability and accuracy of the evaluation result are improved.