53 results about "Health knowledge" patented technology

A computer-implemented system for personalized health optimization constructs a confidence-weighted personal health knowledge graph (PHKG) from heterogeneous data, including wearable sensors, medical devices, lab results, medication logs, and conversational inputs. A multi-stage causal-inference stack identifies modifiable drivers of outcomes using layered methods (e.g., MI, GAM, Neural Granger, DAG-GNN), and simulates candidate interventions. A recommendation engine ranks lifestyle or pharmacologic actions using a benefit-to-friction score, selecting a personalized intervention aligned with user readiness and clinical safety constraints. Interventions may include a minimum effective dose (MED), optimal level, adaptive low-dose, or behavioral challenge. Optional modules include reinforcement learning for timing adaptation and privacy-preserving on-device inference. The system operates across domains including metabolic, cardiovascular, renal, sleep, stress, and medication response, enabling cross-condition synergy evaluation. The architecture is modular, supports runtime plug-in targets, and adapts in real time with or without continuous clinical oversight, depending on deployment.

The invention belongs to the technical field of medical treatment and public health, and particularly relates to a hypertension group knowledge recommendation method and system based on a large language model multi-agent. Hypertension knowledge question-answer pair information, medical short video information and user personal health portraits are finely extracted by constructing a hypertension knowledge question-answer pair library; according to the method, video content quality evaluation and matching degree evaluation are performed, and user platform interaction data adjustment is combined, so that personalized and accurate knowledge recommendation services can be provided for hypertension users, the requirements of hypertension patients for health knowledge are met, the accuracy and effectiveness of knowledge recommendation are improved, and self-health management of the patients is facilitated.

The invention relates to the technical field of data processing and analysis, in particular to an intelligent large health system and a data processing method thereof, and the method comprises the steps: collecting the data of a multi-source heterogeneous data source in real time, and comprehensively capturing the multi-dimensional health data of a user; a multi-modal health knowledge graph is dynamically constructed and optimized through an efficient data preprocessing and feature alignment technology, and the integration value and the utilization efficiency of data are improved; a graph neural network and a time sequence analysis model are utilized to realize accurate evaluation of the health state of the user and timely prediction of future risks, and predictability and pertinence of health management are effectively improved; based on a reinforcement learning algorithm, a highly personalized intervention sequence can be generated according to the individual condition of a user, the accuracy of health intervention is enhanced, and the positive change of the health behavior of the user is promoted; an intervention instruction is executed through intelligent equipment, user feedback is monitored in real time, an intervention strategy is dynamically adjusted, and the flexibility and adaptability of intervention measures are ensured.

The invention provides a health state evaluation and product matching method and system based on a knowledge graph, and relates to the technical field of knowledge graphs, and the method comprises the steps: obtaining user health data, building a health knowledge graph, mapping the user data into a feature vector, and employing a multi-scale time convolution network to extract a time sequence change feature; and constructing a dynamic health feature association network, generating a health state evaluation result by using a graph convolutional neural network and a causal discovery algorithm, calculating a collaborative enhancement coefficient based on a product feature vector, and predicting an intervention effect to determine an optimal product combination. According to the method, personalized health assessment and precise product matching are realized, and the health management efficiency is improved.

The invention relates to the technical field of old-age care monitoring, and discloses an intelligent old-age care monitoring method and system based on wearable equipment. According to the method, original physiological data such as heart rate signals, oxyhemoglobin saturation and body movement frequency are collected through a plurality of wearable devices, multi-modal feature extraction is conducted on the original physiological data, and a physiological feature vector set is generated. A to-be-analyzed health event sequence containing a periodic abnormal mode and a non-periodic burst mode is screened out, and a health knowledge base is called to retrieve a matched candidate health event entry set. And inputting the two health events into a health event aggregator for cross-modal semantic fusion analysis, generating a health event decision coding matrix, obtaining an intervention measure instruction set for each health event to be analyzed through hierarchical decoding, and finally generating a response operation queue executable by the pension monitoring terminal. According to the method, the health condition of the old people can be comprehensively and accurately monitored, intervention measures can be timely and effectively provided, and the quality and efficiency of old-age care monitoring are greatly improved.

The invention discloses an intelligent recommendation system for health management, which belongs to the technical field of intelligent medical treatment and comprises an acquisition module, a knowledge analysis module, a calculation processing module and an interaction module. The system collects original health data, manages a health knowledge graph and a safety recommendation rule base, constructs an initial health portrait by using the original health data, generates a first recommendation list and a second recommendation list based on the initial health portrait and a logic rule base, generates a recommendation card through the first recommendation list and the second recommendation list, and sends the recommendation card to a user. And collecting user behavior data for feedback. According to the method, the problems of high cold start difficulty, insufficient safety guarantee and limited personalized effect in the existing health recommendation service are solved, the initial availability and recommendation scientificity of the system are improved, the health behavior of the user can be effectively guided, and the method has positive significance in improving the health level of people.

The invention is suitable for the technical field of artificial intelligence, and provides a medical and cross-boundary fusion-based multimedia data generation method and system suitable for aging, and the method comprises the steps: constructing and training an adaptation degree evaluation model which takes health knowledge features and cross-boundary content features as input and takes the adaptation degree between the health knowledge features and the cross-boundary content features as output; obtaining target health knowledge data and a candidate cross-border content data set, and determining an adaptation degree predicted value of each candidate cross-border content data in the candidate cross-border content data set based on the adaptation degree evaluation model; and determining target cross-border content data based on the adaptation degree predicted value of each candidate cross-border content data, and generating aging-suitable multimedia data based on the target health knowledge data, the target cross-border content data and an adaptation degree evaluation model. According to the technical scheme provided by the invention, the accuracy of health knowledge and cross-border content suitability evaluation is improved, the quality of the multimedia data suitable for aging and the matching degree with the elderly user are improved, and the transmission effect of the multimedia data suitable for aging is improved.

The invention provides a hospital health education intelligent question and answer method based on a large language model and a knowledge base, and belongs to the technical field of intelligent question and answer, and the method comprises the steps: collecting hospital health education related document data for preprocessing, and converting a text block into a vector form through a vector embedding model, storing in an AI native database in combination with metadata, and constructing an index to form a hospital health education knowledge base; receiving health consultation questions input by a user, performing semantic analysis and keyword extraction, and retrieving related knowledge fragments from a hospital health education knowledge base; carrying out fusion reordering on the retrieved knowledge fragments, calculating correlation scores, and selecting the first K knowledge fragments with the highest scores; and substituting the selected knowledge fragments and the user question into a preset cue word engineering template, generating a cue word input large language model, generating an answer for the user question, and feeding back the answer to the user. The acceptability and practicability of the patient on health knowledge are enhanced, and the efficiency of hospital health education and the satisfaction degree of the patient are improved.

The invention discloses a multi-modal health knowledge generation and integration system, which is applied to the technical field of fusion and application of health data, and comprises a multi-modal data acquisition and preprocessing module used for acquiring multi-modal health data and preprocessing the multi-modal health data; the multi-level fusion framework design sub-module comprises data-level fusion based on a time alignment algorithm, feature-level fusion based on a Transform cross-modal attention mechanism and decision-making-level fusion based on an ensemble learning algorithm; and the intelligent knowledge generation sub-module comprises health knowledge graph construction based on a graph neural network, personalized health risk report and intervention scheme generation based on a conditional generative adversarial network, visual image feature contribution degree based on gradient weighted class activation mapping and text data key factor analysis based on an SHAP value. According to the method, the bottleneck of a data island is fundamentally broken through, and the generation quality and the application value of health knowledge are improved.

1. The name of the design product: playing cards (sports guide version). 2. The use of the design product: playing cards for popularizing diabetes health knowledge. 3. The design points of the design product: in the pattern. 4. The picture or photo that best indicates the design points: component 1 front view. 5. The design product is a thin product, and the top view, bottom view, left view, and right view of components 1-56 are omitted; the rear view of components 2-56 is the same as the rear view of component 1, and the rear view of components 2-56 is omitted.

The invention discloses an intelligent popular science knowledge pushing system based on inspection report data. The system comprises a report data acquisition module, a data analysis and feature extraction module, a knowledge graph construction and management module, an intelligent matching and reasoning engine, a user portrait module and a personalized pushing and feedback module. The method comprises the following steps: acquiring a structured or unstructured examination report of a user, and analyzing and extracting key medical entities and numerical features by using a natural language processing technology; precisely screening out popular science knowledge most related to the current health condition of the user; and in combination with a user portrait, personalized pushing is carried out through an optimal channel at an optimal opportunity, and user feedback is collected to optimize the system. According to the method and the system, the problems of generalization of existing health science popularization pushing and disjunction with a personal examination result of the user are solved, accurate, timely, dynamic and personalized health knowledge service is realized, and the health management consciousness and compliance of the user are remarkably improved.

The application discloses a personalized pet nutrition and health care product recommendation method and system, and relates to the field of artificial intelligence. The specific steps comprise the following steps: collecting pet related information and labels from multiple source systems; performing normalization and nonlinear interaction feature construction on numerical features, and performing adaptive embedding and category cross on category type features to obtain enhanced original vectors; screening features by using label association information, and performing clustering fusion to obtain a fusion feature matrix; adopting an improved feature cross network, introducing low-rank decomposition and pet health knowledge prior to construct a classification model; constructing a loss function introducing a rule constraint regular term, training the model and updating parameters; and recommending nutrition and health care products to pets by using the trained model. The application can accurately capture the complex relationship between features, and significantly improve the accuracy of model prediction.

A personal health system, method and device that maintains a health knowledge base, inputs user characteristics, generates health scores based on the user characteristics and provides recommendations based on the user characteristics, health scores and knowledge base, wherein the recommendations are indicated by the knowledge base to be likely to improve the user's health.

The invention provides an information recommendation method and system based on artificial intelligence, and belongs to the technical field of information recommendation. Comprising the steps of 1, constructing a first data set; 2, constructing a second data set; step 3, based on the first data set, constructing a health knowledge preference coefficient of the ith old person; 4, constructing a health behavior adaptation coefficient and a participation depth coefficient of the ith old person based on the second data set; and step 5, associating the ith old people health knowledge preference coefficient with the ith old people health behavior adaptation coefficient and the participation depth coefficient, constructing a comprehensive health participation index, and performing evaluation and optimization. Through data analysis in which online health knowledge and offline medical lectures are combined, the health behavior tendency of the elderly user can be evaluated more accurately, and the optimized recommendation can help the user to obtain appropriate health knowledge.

The invention discloses a large-model wearable electrocardiogram monitoring system and method based on a BSS-CNN-RF-DT-LLM fusion technology. The system comprises hardware equipment and a software platform. The hardware equipment integrates various core algorithm chips and sensing, transmission and interaction modules, and the software platform comprises a plurality of knowledge bases, a plurality of intelligent algorithm systems and a plurality of electrocardiosignal monitoring systems. According to the method, electrocardiosignals are collected through a wearable device, artifacts are removed through a BSS algorithm, features are extracted through a CNN algorithm, a classification model is constructed through an RF-DT algorithm, a professional knowledge report is generated in combination with an LLM algorithm and a health knowledge base, and the professional knowledge report is visually displayed in a partition mode on a display screen. All-dimensional monitoring of multiple electrocardiogram indexes and three-level evaluation of'normal-abnormity-danger 'are achieved, the anti-interference capacity is high, diagnosis is accurate, active monitoring and historical data comparison are supported, operation is convenient and fast, and a reliable solution is provided for daily health management and chronic disease tracking.

1. Name of the product in this design: Playing Cards (Nutritional Science Edition). 2. Purpose of this design: Playing cards for popularizing nutritional and health knowledge. 3. The key design feature of this product is its pattern. 4. The image or photograph that best illustrates the design highlights: Component 1 main view. 5. This design is for a thin product, so the top view, bottom view, left view, and right view of components 1-55 are omitted; the rear view of components 2-55 is the same as the rear view of component 1, so the rear view of components 2-55 is omitted.

The invention relates to the technical field of health monitoring, in particular to an intelligent wearable health monitoring method and system based on artificial intelligence, and the method comprises the steps: collecting multi-modal physiological parameters and behavior data of a user through an intelligent wearable device, constructing a nonlinear mapping relation between health indexes and behavior data, and forming a personalized health state model; and based on the model, optimizing and solving a health early-warning threshold adaptive to the individual user, generating a target early-warning parameter and configuring the target early-warning parameter to the equipment, thereby realizing real-time dynamic monitoring and abnormal early-warning of the physiological parameters. In daily monitoring, physiological and behavior data are analyzed through trends, and intervention suggestions are generated for abnormal fluctuation or potential risks; and meanwhile, user historical health data and a medical diagnosis result are integrated, a health state model is corrected by using big data analysis, and the modeling precision is improved. And in combination with different user group characteristics, a personalized health knowledge base and a case base are constructed, a standardized health assessment scheme is formed, and the accuracy and the intelligent level of personalized health management are improved.

This application discloses a central robot and its home-based health and elderly care implementation method. The method includes: acquiring a user's health events based on multimodal perception data from multiple non-visual sensors, detection data from health monitoring devices, and a digital twin space; activating visual sensors when preset conditions are met, and performing fusion processing with the digital twin space and the user's health profile to obtain the user's scene context; generating health intervention content based on the scene context and a pre-stored health knowledge graph, and mobilizing corresponding execution modules for multimodal output; determining the user's interaction information based on the perception data from the sensing modules and the digital twin space, and adjusting the corresponding execution modules for multimodal output. Implementing the technical solution of this application can avoid errors in perception from a single device or module, reduce the risk of user privacy leakage, provide more professional closed-loop health services, and eliminate the need for complex user operations.

1.The name of the design product: rotating bulletin board (mental health education). 2.The use of the design product: display and dissemination of mental health knowledge. 3.The design points of the design product: in the perspective. 4.The picture or photo that best indicates the design points: perspective. 5.The design contains colors.

The application relates to the technical field of old-age care monitoring, and discloses a smart old-age care monitoring method and system based on wearable devices. The method collects original physiological data such as heart rate signals, blood oxygen saturation and body motion frequency through multiple wearable devices, carries out multi-modal feature extraction on the original physiological data, and generates a physiological feature vector set. A to-be-analyzed health event sequence containing a periodic abnormal mode and a non-periodic burst mode is screened out from the physiological feature vector set, a matched candidate health event item set is searched from a health knowledge base, and the two are input into a health event aggregator for cross-modal semantic fusion analysis to generate a health event decision encoding matrix. The health event decision encoding matrix is subjected to hierarchical decoding to obtain an intervention measure instruction set for each to-be-analyzed health event, and finally a response operation queue executable by an old-age care monitoring terminal is generated. The method can comprehensively and accurately monitor the health status of the elderly, timely and effectively provide intervention measures, and greatly improves the quality and efficiency of old-age care monitoring.

This invention relates to the field of consultation technology, and in particular to a health consultation method and system. The invention constructs a health knowledge graph; parses user input information to identify user intent; generates Cypher query statements based on the obtained user intent; and retrieves the knowledge graph through the Cypher query statements to generate answers. This not only helps improve the accuracy of question and answer but also helps to alleviate the pressure of consultation to a certain extent.

The embodiment of the invention provides a dietary therapy scheme conflict detection method based on traditional Chinese medicine and western medicine and a computer program product, and relates to the field of data processing, and the method comprises the steps: building a user health portrait, determining health knowledge related to the user health portrait, and obtaining a dietary therapy scheme conflict detection result based on the health knowledge and the user health portrait; and conflict information between the diet information and the sign information in the user health portrait and conflict information between the diet information and the medication information in the user health portrait are determined. According to the invention, knowledge of traditional Chinese medicine and western medicine can be combined at the same time, and automatic dietary therapy scheme conflict early warning is realized.

This invention provides a method for intelligently generating health knowledge video personalities (IPs). It involves extracting features from acquired multimodal behavioral data to obtain user feature vectors; constructing a candidate pool based on textual, visual, behavioral, and professional qualification data of multiple health knowledge video personalities (IPs), and calculating the attribute feature vectors of all IPs in the candidate pool; inputting the user feature vectors and the attribute feature vectors of all IPs in the candidate pool into a trained bimodal Transformer fusion model for prediction, obtaining a fit score for each feature vector; sorting all fit scores in descending order, selecting the top few IP recommendation schemes, and using all IP recommendation schemes to fine-tune the attribute feature vectors of all IPs in the candidate pool to generate health knowledge video personality (IP) schemes; thereby improving the accuracy of IP matching with user needs and enhancing the dissemination effect of health knowledge.

The invention provides an equipment health maintenance decision-making method and system based on a dynamic knowledge graph, and relates to the technical field of industrial equipment health management.The method comprises the steps that firstly, an equipment real-time state data set of a distributed industrial equipment cluster is obtained, and an equipment health ontology model is constructed; performing knowledge extraction and fusion on the equipment operation parameter record and the abnormal event log record in the equipment real-time state data set, dynamically constructing an equipment health knowledge graph, inputting the current equipment real-time state data into the knowledge graph for matching reasoning, generating an equipment health diagnosis reasoning result, and outputting the equipment health diagnosis reasoning result. And finally generating an equipment maintenance decision instruction set based on the equipment health diagnosis result, and sending the instruction set to an execution terminal. The device state can be comprehensively mastered, the fault root cause can be accurately positioned, the maintenance decision can be scientifically made, the device maintenance efficiency and accuracy can be improved, and the production continuity can be guaranteed.

The invention provides a health knowledge video character IP intelligent generation method, and the method comprises the steps: carrying out the feature extraction of obtained multi-modal behavior data, and obtaining a user feature vector; constructing a candidate pool based on the text data, the visual data, the behavior data and the professional qualification data of the plurality of health knowledge video character IPs, and calculating attribute feature vectors of all the character IPs in the candidate pool; inputting the user feature vectors and attribute feature vectors of all character IPs in the candidate pool into a trained bimodal Transform fusion model for prediction, and obtaining an adaptation score of each feature vector; sorting all the adaptive scores according to a descending order, selecting a plurality of first IP recommendation schemes, performing fine adjustment on attribute feature vectors of all character IPs in the candidate pool by using all the IP recommendation schemes, and generating a health knowledge video character IP scheme; therefore, the adaptation precision of the IP and the user demand is improved, and the health knowledge spreading effect is enhanced.

The invention discloses a health knowledge base construction method and system and a health report interpretation method and system, belongs to a retrieval enhancement generation technology, and aims at solving the problems that an existing knowledge base is small in application range, and the interpretation accuracy is low when report interpretation is conducted through the knowledge base. When a knowledge base is constructed, a knowledge text created by the method is an original created table or a knowledge table obtained after an original knowledge table or a previous updated knowledge table is updated by an interpretation result obtained after report interpretation is carried out on the knowledge base constructed by the original knowledge table or the previous updated knowledge table; and carrying out special coding on the item ID numbers in the table, then setting a text index, and slicing according to rows to obtain a knowledge base. The knowledge base constructed through the method can be suitable for interpretation of different hospital clinical laboratory reports at the same time, the application range of the knowledge base is larger, and the report interpretation accuracy is higher when the knowledge base is used for report interpretation.

The present application belongs to the technical field of data analysis, and discloses a health state evaluation method and system based on physical sign data. The method comprises the following steps: constructing a physical sign health knowledge graph, a physical sign data health evaluation model, a health evaluation result optimization model, and a rehabilitation training strategy generation model; using the physical sign health knowledge graph to perform knowledge expansion on real-time physical sign data; using the physical sign data health evaluation model to perform physical sign data health evaluation according to the knowledge-expanded real-time physical sign data; using the health evaluation result optimization model to perform health evaluation result optimization according to a plurality of real-time physical sign data health evaluation results; and using the rehabilitation training strategy generation model to perform rehabilitation training strategy generation according to the optimal real-time physical sign data health evaluation result, thereby obtaining a real-time rehabilitation training strategy. The present application solves the problems of low efficiency, low accuracy, and lack of response mechanism in the prior art.

The application relates to the technical field of health information, and discloses a personalized health suggestion generation algorithm based on multidimensional health data, which comprises the following steps: constructing a comprehensive context feature vector of a user; combining historical behavior data of the user to quantize personalized health resistance of the user when participating in various health activities; applying an inverse reinforcement learning algorithm to inversely deduce an implicit health preference reward function of the user based on a historical health decision sequence of the user; applying a multi-objective optimization strategy generation strategy to candidate health activities based on a health knowledge graph, personalized health resistance and the implicit health preference reward function to obtain a personalized health suggestion scheme; and iteratively updating the quantization model of the personalized health resistance and the implicit health preference reward function based on feedback data of the user after the user performs health activities according to the scheme; and the application can improve the efficiency of personalized health suggestion generation based on multidimensional health data.

The invention relates to the technical field of intelligent health management, and discloses an artificial intelligence-based twenty-four solar term health guidance system, which comprises a map construction module, a health state prediction module, a solar term conversion early warning module, a scheme generation module, an interaction and push module and a system optimization module. A solar term health preserving knowledge graph is constructed by collecting solar term health preserving data and multi-source health data, feature extraction is performed by using a bidirectional long-short term memory network and a graph attention network, and solar term health state prediction is realized; a Bayesian reasoning framework is adopted to fuse the historical same-period health mode and the weather forecast data, and graded risk early warning information is generated; generating a personalized health maintenance scheme combination through a multi-objective optimization algorithm; multi-modal emotion recognition and scene perception technologies are adopted to realize emotional interactive pushing; and continuously optimizing the prediction model and the recommendation strategy based on user feedback data. According to the invention, prospective health risk early warning and personalized health maintenance guidance can be provided in the sensitive period of solar term conversion, and the accuracy and effectiveness of user health management are improved.

This invention relates to a cardiovascular health management method and system that integrates a smartwatch and a WeChat mini-program, comprising: (1) the smartwatch collects real-time cardiovascular-related physiological and behavioral data from the user and transmits it to the WeChat mini-program in a standard format using 4G IoT communication technology; (2) the WeChat mini-program provides multi-dimensional user interaction functions, including health behavior check-in, health knowledge learning, and community communication and interaction; (3) through the two-way linkage between the smartwatch and the mini-program, a closed-loop cardiovascular health management process of "data collection - interactive participation - professional intervention - effect tracking - plan optimization" is constructed to achieve full-cycle digital intelligent management of the user's cardiovascular health. It can achieve efficient and stable data interoperability between the smartwatch and the WeChat mini-program, comprehensively meet the user's full-cycle cardiovascular health management needs, provide precise and real-time health management solutions, and improve the user's long-term participation compliance.