36 results about "Health knowledge" patented technology

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 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 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 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.

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 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.

The application belongs to the technical field of medical health, and particularly relates to a hypertension group knowledge recommendation method and system based on a large language model multi-agent, which can provide personalized and accurate knowledge recommendation services for hypertension users by constructing a hypertension knowledge question and answer pair library, finely extracting hypertension knowledge question and answer pair information, medical short video information and user personal health portraits, performing video content quality evaluation and matching degree evaluation, and adjusting in combination with user platform interaction data, meet the needs of hypertension patients for health knowledge, improve the accuracy and effectiveness of knowledge recommendation, and help patients with self-health management.

The invention relates to the field of agricultural life education interaction, in particular to an agricultural life education interaction platform system based on an ecological solar term ceremony order. Comprising a solar term culture knowledge base module, an interactive curriculum generation module, a farming operation simulation and guidance module, a food cultivation and health knowledge module, a ceremony order behavior guidance module, a curriculum task clock-in and excitation system, a data statistics and growth file module, a user management module and a central control module. According to the agricultural life education interactive platform system based on the ecological solar term ceremony order, a modularized system integrating solar term culture, farming operation, food and cultivation health and ceremony order behaviors is constructed, so that the situation that traditional agricultural education is fragmented in content and light in cultural connotation is changed; according to the method, deep integration and situational pushing of solar term-farming-culture-health multi-dimensional knowledge are realized, so that a user can systematically understand ecological logic and culture significance behind the user while learning farming skills, and the culture thickness and cognitive integrity of education are remarkably improved.

The invention relates to the technical field of health detection and early warning. The individual health early warning method and system integrating physiological monitoring and behavior questionnaires comprises the steps that physiological, behavior and environment data of a user are collected; constructing a personal health knowledge graph fused with medical knowledge; establishing a mechanism and data driving fused digital twinborn model based on the atlas, and performing dynamic risk assessment and traceability; and simulating and deducing in the digital twinning according to the result to generate a personalized intervention plan, and forming closed-loop optimization. The system comprises an edge sensing layer, a cloud intelligent center layer, an application service layer and an ecological interface layer. According to the invention, full-process health management from multi-source data fusion, intelligent risk assessment to personalized intervention closed loop is realized, and the accuracy, foresight and effectiveness of health early warning are improved.

The invention relates to the technical field of health management and artificial intelligence, and discloses a personalized food combination matching method and system based on deep learning, and the method comprises the steps: obtaining real-time physiological indexes and historical diet data of a user, and constructing a user health knowledge system; calculating a dynamic demand weight according to the knowledge system to determine a constraint condition priority; and finally, carrying out weight fusion and verification through multi-stage verification and adjustment such as dynamic optimization, consistency evaluation and sequence generation, so as to obtain a final personalized food combination scheme. The method can dynamically adapt to the personalized needs of the user, and the accuracy of the diet scheme and the health goal achievement rate are remarkably improved.

The invention provides a health question and answer method and system based on knowledge graph and large language model fusion, and the method comprises the steps: analyzing a query request inputted by a user, and obtaining a query intention related to a query content; querying context information associated with the query intention from a health knowledge graph; the context information and the query content are input into a prompt template, the prompt template comprises a constraint instruction used for constraining behaviors of the first large language model, and the constraint instruction is used for enabling answer content of the model to be only related to the context information; and inputting the prompt template into the first large language model to obtain reply content corresponding to the query request fed back to the user. The method provided by the invention is applied. According to the intelligent health question-answering system, the structured and high-credibility facts of the personal health knowledge graph can be effectively combined with the powerful natural language processing capability of a large language model, so that the intelligent health question-answering system which can ensure that the answer content facts are accurate and highly personalized and can provide smooth and natural interactive experience is realized.

The invention relates to the technical field of campus digital health management, in particular to an intelligent health campus management system and method based on gridding management, and the system comprises a gridding space and personnel organization mapping module which is used for carrying out the gridding of a campus physical space, so as to obtain a multi-level management grid, mapping is carried out according to an administrative organization so as to generate a campus space digital management platform; the multi-source heterogeneous health data acquisition and fusion module is used for acquiring multi-source heterogeneous data in the platform so as to construct a personal health electronic file; the health risk assessment and hospital guide module is used for predicting a health risk prediction result and personalized triage suggestions of each individual according to the personal health electronic archives; and the service touch and intervention module is used for pushing health knowledge or activities and sending personalized triage suggestions to a grid responsible person or a corresponding professional institution. Therefore, the problems of data islands, service passivity and fragmentation and the like in existing college health management are solved.

1. The name of the design product: plastic fan. 2. The use of the design product: for fan, with health knowledge dissemination. 3. The design points of the design product: in the combination of shape and pattern. 4. The picture or photo that best indicates the design points: perspective drawing.

The application relates to the technical field of medical information, and discloses an early warning method for discovering health risks based on WeChat for enterprises and AI, which comprises the following steps: constructing a health knowledge base; constructing a customer health portrait; collecting multi-modal interaction content in a WeChat for enterprise session in real time, performing deep semantic analysis, and outputting preliminary health risk labels; performing multi-dimensional risk reasoning on the preliminary health risk labels to generate a comprehensive risk assessment result; generating individualized intervention suggestions, triggering a hierarchical early warning mechanism, and distributing structured early warning information; and verifying accuracy to drive continuous optimization of the model. According to the scheme, multi-source medical knowledge, dynamic customer portraits and multi-modal context semantic analysis are combined to realize accurate identification of hidden health risks, individual health trajectories and a three-dimensional evaluation framework are combined to distinguish context differences, adapt to the expression habits of different groups of people, reduce misjudgment and false negatives, and through a closed-loop intervention and a federal optimization mechanism, fine, interpretable and highly compliant health risk early warning is realized.

The invention provides a nutrition measurement and diet recommendation platform and method based on a multi-modal large language model, and the platform comprises an input information obtaining module which is used for obtaining word information, statement information and / or picture information inputted by a user in a plurality of target input regions, and is used for analyzing the word information, statement information and / or picture information, and sending the analyzed word information, statement information and / or picture information to a user terminal; determining at least one target food type and food quantity; the nutrition analysis module is used for determining the nutrient element quantity and the dynamic evaluation result of the user according to the at least one target food type and the food quantity, and is used for determining the health risk index of the user according to the nutrient element quantity and the dynamic evaluation result of the user; the health propaganda and education module is used for providing nutrition and health knowledge content; and the diet recommendation module is used for generating highly personalized diet suggestions according to the nutrient element quantity and the dynamic evaluation result of the user, the personal physiological parameters and the health targets. And intelligence, individuation and convenience of nutrition and health management are improved.

The application discloses a health popular science data accurate recommendation method based on big data, relates to the technical field of big data management, and comprises the following steps: collecting health popular science data and performing unified format specification processing and source checking, generating a health popular science basic resource set, simultaneously collecting and uniformly marking user behavior data; performing medical semantic analysis on the health popular science basic resource set, establishing a standard concept association and a reference relationship tracking structure, and constructing a health knowledge semantic index library; performing source tracing and evidence chain integrity checking on health popular science data in the health knowledge semantic index library, forming a health knowledge credible transmission path diagram, determining an effective time period of health popular science data content according to the health knowledge credible transmission path diagram, and generating a health knowledge time-effectiveness decay rule set. The health knowledge credible transmission path diagram can be constructed by performing source tracing and evidence chain integrity checking on health popular science data in the health knowledge semantic index library.