79 results about "Personalized nutrition" patented technology

The invention relates to the technical field of artificial intelligence and nutrition health management, and discloses an intelligent nutrition correction tracking early warning method and system.The intelligent nutrition correction tracking early warning method comprises the steps that a hierarchical heterogeneity causal effect model is constructed, and individual features are mapped to a potential type space; representing a causal relationship between nutrition intervention and result variables by using a structural causal model, and evaluating an intervention effect by using a dual robust estimator; personalized grouping is realized by identifying individual subgroups; a reinforcement learning algorithm based on context awareness is combined with an anti-fact reward function, and a personalized nutrition intervention strategy is optimized; key feature combinations are extracted through a differentiable decision tree and SHAP value analysis, and multi-level causal interpretation is generated. According to the method, anti-factual reasoning, reinforcement learning and causal relationship extraction technologies are fused, accurate prediction, evaluation and early warning of the individual nutrition intervention effect are realized, and the personalized precision of nutrition intervention and the user compliance are remarkably improved.

The invention discloses a customer health data intelligent management system and method, and belongs to the technical field of health data management. Basic data and health data are collected; the client inputs a daily menu and calculates nutrients; establishing a daily nutrient matrix based on nutrients, and identifying a diet mode; defining a taste space, and extracting taste features based on the seasoning use condition of the menu every day; integrating to form an input vector; establishing a personalized nutrition demand prediction model, and training to obtain nutrition constraints; retrieving the candidate recipes based on nutrition constraints, and performing taste matching to obtain recommended recipes; based on the menu selection records of the similar clients, the recommended menu is optimized; dynamically adjusting the recommendation strategy according to the score of the customer for the recommended menu to obtain an optimal menu; when the customer eats the optimal menu, the change of health data before and after diet intervention is calculated, and the intervention effect is quantified; nutrients needed by the client are adjusted based on the intervention effect, and the optimal menu is correspondingly adjusted.

The invention relates to an AI personalized nutrition evaluation and guidance method based on individual continuous diet data. The AI personalized nutrition evaluation and guidance method comprises the following steps: (1) calculating individual single meal food and nutrient intake; individual health indexes are collected, the individual daily energy demand amount is calculated, and the daily food and nutrient demand amount is determined; (2) carrying out instant personalized nutrition evaluation on food and nutrients ingested by an individual in a single meal according to a domestic public recommendation standard; (3) on the basis of individual nutrition and health data continuously recorded in the longitudinal direction of time, establishing a personalized nutrition intake-health model taking an individual as a unit, and carrying out personalized nutrition evaluation and health risk prompting; and (4) simulating the idea of nutrition guidance of professionals to create an AI nutrition guidance algorithm, and generating AI guidance. By adopting the AI personalized nutrition evaluation and guidance method based on the individual continuous diet data, a sustainable AI-assisted diet self-management solution suitable for daily life scenes is effectively provided.

The invention discloses a health data analysis and nutrition recipe generation method based on an enhanced large model, and the method comprises the steps: constructing an enhanced large language model, and obtaining an optimal autoregression language model according to an optimized multi-source heterogeneous data set; constructing a medical nutrition knowledge graph to fuse the structured data and the unstructured data of the medical nutrition to obtain an optimized medical nutrition knowledge graph; according to the optimized multi-source heterogeneous data set, constructing a user health portrait used for obtaining multi-dimensional health features of the user; and constructing a user health state time sequence prediction model to obtain user health state data, and obtaining a personalized nutrition recipe in combination with the optimized medical nutrition knowledge graph. The problems that in a traditional method, a data source of health data analysis is single, integration of multi-source heterogeneous data is lacked, the health condition of an individual is difficult to comprehensively reflect, knowledge coverage of the generated recommended recipe is incomplete, the illusion phenomenon is likely to be generated, and the generated recipe is insufficient in pertinence and scientificity are solved.

The invention relates to the technical field of artificial intelligence, and discloses a system of a nutrition recipe recommendation system based on artificial intelligence in chronic disease intervention management and an application method. Comprising a data acquisition module, a data preprocessing and feature engineering module, a knowledge base management module, a personalized nutritional requirement modeling module, a recipe generation and optimization module, a user interface module and a model training and updating module which are in communication connection through a network. According to the method, personalized health data such as physiological indexes, chronic disease characteristics, diet preference, allergy and intolerance information of a user are collected in multiple dimensions, a nonlinear relation between the characteristics of the user and nutritional requirements is deeply mined in combination with a deep learning model, and an accurate personalized nutritional requirement model is generated according to specific illness conditions and body indexes of different chronic disease patients; therefore, recipe recommendation conforming to individual differences is provided, and the risk of aggravating the illness state due to improper diet is reduced.

The invention relates to the technical field of nutritious food configuration, and discloses a system and a method for configuring personalized nutritious food, and the method for configuring personalized nutritious food comprises the following steps: collecting spectral characteristic data and chemical component data of a food material sample by adopting a hyperspectral imaging and mass spectrum combined technology, and obtaining holographic chemical fingerprint information; processing the collected spectral data by using a multi-scale feature extraction algorithm, extracting multi-level feature information of the food materials, and carrying out standardization and dimension reduction processing on the feature data; according to the method, high-precision prediction of the nutrient content of the food material is realized through combination of hyperspectral imaging and mass spectrometry technologies and a deep learning model, so that the nutrient content prediction accuracy and the configuration scheme accuracy are improved, the nutrient balance achievement rate is also improved, and meanwhile, the limitation of a static database is broken through; real-time nutritional ingredient analysis of any food material is achieved, the method can adapt to individual differences and freshness changes of the food materials, and accurate configuration based on actual food material characteristics is provided.

The invention provides a CKD nutrition management visual monitoring method and system based on big data, and relates to the technical field of data processing, and the method comprises the steps: carrying out the data preprocessing according to real-time health data, and obtaining a standardized health data set; according to the standardized health data set, evaluating nutritional requirements of the patient, and combining disease progression, individual differences and diet preferences of the patient to generate a personalized nutrition management scheme, the personalized nutrition management scheme including recommended diet, a nutrition supplement scheme and an intake behavior adjustment scheme; according to the personalized nutrition management scheme, a visual display interface is generated, and the visual display interface displays the nutrition state, diet suggestions, potential health risks and predicted effects of the patient; adjusting a personalized nutrition management scheme in real time according to feedback data and health state changes provided by the patient in the use process, and presenting an updated scheme through a visual display interface; the autonomy and accuracy of nutrition management are improved.

The invention provides a precise feeding system and method for animal husbandry, and belongs to the technical field of animal husbandry breeding, the precise feeding system comprises an intelligent feeding terminal, a central control terminal and a plurality of livestock information acquisition terminals, the intelligent feeding terminal is wirelessly connected with the central control terminal, and the livestock information acquisition terminals are wirelessly connected with the central control terminal. The livestock and poultry information collection terminal is used for collecting information of each individual of livestock and poultry and transmitting the collected information to the central control terminal, the central control terminal sends control information to the intelligent feeding terminal according to the information of each individual of the livestock and poultry, and the intelligent feeding terminal carries out quantitative feeding on the livestock and poultry according to instructions and environment information. Through real-time monitoring of livestock and poultry individual information and environmental parameters and in combination with a nutritional requirement model, precise feed feeding of each livestock and poultry is realized, feed waste is avoided, the breeding cost is reduced, meanwhile, personalized nutritional requirements of the livestock and poultry are met, and healthy growth of the livestock and poultry is promoted.

The invention relates to the technical field of diet health services, in particular to a diet service method and system based on human nutriology. The method comprises the steps of collecting multi-dimensional data for a user; on the basis of a human nutriology database and user full-amount data, a personalized nutrition target is determined through nutrition requirement calculation; in combination with personalized nutrition targets, user dietary habits and actual life scenes, food material recipes are matched to generate multiple sets of personalized dietary schemes; providing diet scheme execution guidance, and adjusting the diet scheme; the personalized diet scheme and the updating scheme are pushed to the user; the system comprises a user data acquisition module, a nutrition target determination module, a diet scheme generation module, a diet scheme guidance and dynamic adjustment module and a push module. According to the method, multi-dimensional adaptation of nutritional demand analysis to user data is realized, the disease state, exercise intensity and dietary habits of the user are fully combined, the nutrition target pertinence is improved, and the actual demand of the user is accurately matched.

The invention relates to the technical field of breeding, in particular to a livestock head data analysis and management system in the breeding process. Compared with the prior art that a group unified feeding scheme is adopted, individual development differences and environment variables cannot be responded, and double resources are wasted due to insufficient nutrition of high-value livestock and excessive feeding of low-efficiency individuals; according to the scheme, a personalized nutrition demand modeling and formula optimization engine is initiated for the first time, the metabolic state is inversed by analyzing 3D features of the head in real time, the protein energy ratio and the environment compensation coefficient are dynamically calculated, a linear programming solver is linked to generate the lowest-cost formula, the feeding time sequence is adaptively adjusted, and the accurate nutrition supply mode of one animal and one strategy is thoroughly reconstructed; the feed conversion rate and the breeding economic benefit are obviously improved.

The present invention includes techniques for food image processing and particularly relates to a method and system for personalized nutrition management with food image recognition models using deep learning. The method comprises: a user side obtains an food image to be taken by a user, and the food image is input into a trained food image recognition models using deep learning to obtain different types of food sub-images; computing the amount of nutrients contained in the food sub-images, and accumulating the nutrients in all the food to obtain the total nutrients intake of the user; setting intake thresholds of various nutrients, and comparing the total intake of various nutrients with corresponding nutrient intake thresholds to obtain a comparison result; according to the comparison result, type and quantity of taken food are adjusted, and nutrition management is completed. The invention associates the food intake information uploaded by the user with other data sets (e.g., recommendations from their nutritional physician) through the server to determine whether the obtained energy and nutrient ratio are appropriate, and finally, the analyzed data is feedbacked to the user, thereby prompting the user to improve the diet plan.

The invention relates to the technical field of artificial intelligence, in particular to a long-term healthy diet recommendation method, device and system and a medium, and the method comprises the steps: obtaining the current original data of a user, carrying out the preprocessing of the original data, and generating a health data vector of the user; dividing the life cycle into different life stages, and determining a standard nutritional requirement vector of each life stage; determining a life stage of the user, and generating a personalized nutritional demand vector of the user based on the standard nutritional demand vector of the life stage and the health data vector of the user; acquiring historical data of the user, generating a comprehensive feature vector based on the historical data, and generating a prediction result of the current life stage of the user based on the personalized nutritional demand vector and the comprehensive feature vector; generating a current diet planning scheme of the user based on the personalized nutritional demand vector of the user in the current life stage; according to the invention, continuous optimization and evolution of long-term healthy diet planning can be realized.

Provided herein are methods for providing personalized nutritional supplementation to a subject. Also provided are compositions of personalized nutritional supplementation for subjects in need thereof.

The application discloses a formula food operation and management device based on human-computer interaction technology, which comprises a human-computer interaction module, a nutrition analysis module, a formula food screening module and a formula food mixing module which are connected in communication. The detailed health information collected by the human-computer interaction module can provide highly personalized nutrition matching information through the nutrition analysis module, so that the postoperative patient can obtain the most suitable nutrition supply for recovery needs. For special nutritional needs that cannot be met directly through standard full-nutrition formula food, the formula food screening module can be combined with a nutrient component matching prediction model to dynamically generate customized nutrient component mixing matching parameters, thereby solving the problem that it is difficult to configure under the traditional method.

The invention provides a nutrition balance evaluation method and system for dish matching, a storage medium and equipment, and the system can generate a personalized nutrition demand threshold model for each user through creating a detailed user file and constructing a multi-dimensional health portrait, provides nutrition optimization suggestions conforming to individual health conditions and diet preferences, and improves the user experience. Meanwhile, by combining a preset dietary nutrition standard table and a preset food material nutrition database, the system calculates the food material nutrition content in real time and performs dynamic correction, the accuracy and reliability of nutrition data are ensured, nutrition complementation food material screening and component adjustment calculation are performed by utilizing a learning algorithm, and the accuracy and reliability of nutrition complementation are improved. In addition, factors such as allergen information, religious diet taboo, interaction of active ingredients of food materials and the like of the user are fully considered, and feasibility and safety of the optimization suggestion are ensured.

The invention provides a nutrition scheme recommendation method and device based on a large language model and electronic equipment, and relates to the technical field of artificial intelligence and digital health, and the method comprises the steps: obtaining multi-modal input data according to a preset period; analyzing the multi-modal input data based on the multi-modal fusion model to generate a user state vector; fusing the user state vector and the user input through a soft prompt tuning technology to generate a customized prompt word; analyzing the customized cue word based on a large language model of a retrieval enhancement generation framework, accessing an external nutriology database, and outputting personalized nutrition recommendation content; and performing structured processing and visual output on the nutrition recommendation content, and performing iterative optimization on the model parameters based on user feedback data. According to the invention, through organic combination of technologies of multi-modal information fusion, soft prompt tuning, retrieval enhancement generation and the like, generation of a nutrition recommendation scheme which is highly personalized, dynamically adaptive and good in user experience is realized.

A system (100) and method (900) for dispensing a personalized nutraceutical (81) to a consumer (62). The system (100) can create the personalized nutraceutical (81) that is selectively influenced by one or more health attributes (640) relating to the intended consumer (62) of the personalized nutraceutical (81). The application(s) (373) of the system (300) can create a variety of outputs (690) including a personalized recipe (693) for the personalized nutraceutical (81) from a variety of inputs (610) that can include the health attributes (640) of the consumer (62). A production assembly (500) can manufacture the personalized nutraceutical (81) using the personalized recipe (693).

The principle underlying this method is that the person's health improves when the microbiome within as well as the host is balanced and well-functioning. The method of this disclosure presents lifestyle choices that accommodate the superorganism of person plus microbiome. Examples of lifestyle choices are types of products safest to eat, use and wear, those safest to avoid. The system is simple to use in that it includes the minimum in the form of suggestion lists to reach better health, with links to references for those seeking scientific explanations. Users are asked from time to time to record their lifestyle choices and how their bodies responded. The logic of personalized suggestions derives from the health professional's knowledge and the scientific reference-supported Artificial Intelligence Analyst. The method and system depend upon continual internal and external cross-checks which enhances reliability.

According to the health-care tea extraction machine based on ultrasonic cooperative intelligent temperature control and the multi-mode extraction method, through the ultrasonic-temperature-pressure multi-physical field synergistic effect, the dissolution rate of active ingredients is remarkably increased to 85% or above (30%-40% higher than that of a traditional mode), and meanwhile energy consumption is reduced to 0.05 kWh / time. The intelligent capsule system realizes one-button operation through RFID identification and automatic parameter matching; the double-layer degradable capsule meets the requirements for high temperature resistance and environmental protection, and the degradation period is shortened to be within 90 days. The introduction of the Internet of Things function supports remote monitoring and data analysis, and provides a personalized nutrition report for the user. In addition, the miniature piezoelectric transducer is combined with a PID precise temperature control technology, so that the equipment has high efficiency and household adaptability, and the technical blank of consumer-grade ultrasonic extraction equipment is filled.

The invention discloses a personalized nutrition scheme generation method and system for height increase, and relates to the field of health management, and the method comprises the steps: collecting static biological data, parent height data, health background questionnaire data and intestinal flora samples of a user, calculating the genetic target height and basal metabolic rate of the user according to the static biological data and the parent height data, generating a personal file of the user; extracting height, weight and leg length data of the user from a personal file of the user, obtaining stress distribution of a lower limb epiphyseal plate of the user under different exercise types through biomechanical simulation, and generating a personalized exercise scheme according to a stress distribution result; and estimating daily energy consumption according to the basal metabolic rate and the personalized exercise scheme to obtain the daily total energy demand of the user. According to the method, the problem of insufficient scheme accuracy and adaptability caused by neglecting individual nutrition absorption difference and biomechanical response characteristics in a traditional method is effectively solved.

According to the daily diet nutrition analysis method based on the wireless weighing record, the intelligent nutrition scale can collect the food weight and conduct peeling calculation, and the net diet weight is accurately obtained. Through peeling calculation, weight interference of non-food parts such as containers can be eliminated, it is ensured that data uploaded to a cloud analysis background is the real food weight, and a foundation is laid for follow-up accurate nutrition analysis. The cloud analysis background can record the data in time and bind the data with the user ID, so that the diet data of each user can be independently stored and managed, and subsequent personalized nutrition analysis and health management for the user are facilitated. After the cloud analysis background records the data, a nutrition analysis notice or a food type selection input notice is sent to the user terminal in time. The timely notification mechanism can improve the participation degree and the response speed of the user, and ensures that the whole nutrition analysis process is efficiently carried out. The user can quickly log in the cloud analysis background to perform subsequent operation according to the notification, and waiting time is shortened.

The invention relates to an AI-based method, device and equipment for assisting diet conditioning management and control of chronic diseases of old people and a medium. The method comprises the following steps: collecting multi-dimensional user data, and preprocessing the multi-dimensional user data to obtain a user health file; based on the user health archive, calculating a nutrition health demand of a corresponding user, and obtaining a personalized nutrition target list; calculating a suitability score corresponding to the user for each food material based on the personalized nutrition target list; based on the suitability score, screening the food materials to obtain a safe food material library; based on the safe food material library, performing preliminary screening on a recipe database to obtain a candidate recipe set; constructing an optimization problem based on the personalized nutrition target list and the candidate recipe set; and solving the optimization problem to obtain a recipe scheme. By adopting the method, the complex relationship between the disease and the nutrition constraint can be accurately mined and dynamically matched, and the personalized health requirement of the patient is met.

An intelligent diet management system for children is provided with a user module, a database storage module, a recipe recommendation module, a shopping management module and a recipe recognition module. According to the intelligent diet management system for children, personalized nutrition recommendation can be carried out, the recognition precision and safety are improved in combination with an allergen management mechanism, operation steps are remarkably reduced, a whole-process system covering recipe recommendation, shopping cart management and a distribution calendar is constructed, and seamless connection and efficient landing from recipe generation to actual dining tables are achieved. In addition, the intelligent diet management system for children also realizes accurate identification of recipe contents, improves convenience and scientificity of food material preparation based on ingredient intelligent management, and performs matching with allergy data to perform allergy warning.

The invention relates to the technical field of healthy diet, in particular to an intelligent proportioning and mixing system based on healthy diet. The invention discloses an intelligent proportioning and mixing system based on healthy diet. The intelligent proportioning and mixing system comprises a data processing module, a user interaction module, a food material storage and conveying module, an intelligent proportioning module, an intelligent mixing module and a communication module. The system has the beneficial effects that the data processing module comprehensively analyzes the health information of the user, and uses a professional nutrition proportioning algorithm to accurately calculate the food material dosage, so that the personalized nutrition requirements are met, and the accurate nutrition proportioning is realized; the intelligent mixing module optimizes a mixing mode according to food material characteristics by virtue of a plurality of mixing modes and real-time environmental parameter monitoring, so that the mouth feel and the nutrition absorption are improved; diversified operation of the user interaction module is combined with remote control of the communication module, and operation convenience is greatly improved.

The utility model provides a kind of water and fertilizer integration device for rose planting. The water and fertilizer integration device for rose planting includes: base, fixedly installed with mounting bracket on the base;Water storage tank, the water storage tank is fixedly installed on the base;Multiple fertilizer storage tanks for storing different fertilizers, multiple the fertilizer storage tanks are fixedly installed on the base, multiple the fertilizer storage tanks are equipped with discharge pipe, the discharge pipe is communicated with the water storage tank, and the discharge pipe is equipped with sealing valve;Detection mechanism, the detection mechanism is equipped on the water storage tank, for detecting soil nutrient;Irrigation and fertilization mechanism, the irrigation and fertilization mechanism is equipped on the water storage tank, for irrigation and fertilization to rose. The water and fertilizer integration device for rose planting provided by the utility model can detect soil nutrient before irrigation and fertilization, can prepare water and fertilizer solution according to detection result, provide personalized nutrition supply for rose, and be conducive to the healthy growth of rose.

The invention discloses a wheat growth regulation and yield prediction integrated method based on artificial intelligence, and the method comprises the steps: obtaining wheat growth data and environmental factor data through a sensor network, and carrying out the preprocessing and standardization; utilizing machine learning modeling analysis to identify nutritional requirement change characteristics of the wheat in a growth stage, and determining a trace element ratio adjustment direction; a personalized nutrition supply scheme is generated in combination with a dynamic regulation and control strategy, a regulation and control scheme is optimized through a resource utilization efficiency evaluation model, a field management system is updated, and finally a wheat yield prediction result is obtained in combination with a yield prediction model. According to the method provided by the invention, precise nutrition management in the whole wheat growth process is realized, the resource utilization efficiency is improved, and effective technical support is provided for improving the wheat yield and quality.

The present application relates to the technical field of formula product processing, and in particular to a packaging forming module, a personalized formula product preparation device, and an application. The packaging forming module provided by the present application comprises: an outer layer structure; and an inner layer structure at least partially nested in the outer layer structure and used for receiving raw materials and guiding the raw materials into a packaging container for packaging, wherein the inner layer structure and the outer layer structure are detachably connected or integrally formed. The packaging forming module is assembled in a personalized formula product preparation device, nutrients can be prepared conveniently, rapidly, with low cost, and accurately according to the personalized formula of customers, and wide popularization and application of personalized nutrition customization can be promoted.

The invention discloses a nutrition evaluation and personalized nutrition intervention system for children during hospitalization, and relates to the technical field of medical health information, and the system comprises a terminal which is used for collecting daily multi-omics data, medication data and nutrition intake data of children with metabolic diseases; the monitoring equipment is used for collecting daily growth and development data of the metabolic disease children; the processor is used for outputting daily metabolic capability data and nutrient utilization rate data through a neural network according to the multi-omics data; and according to the metabolic capability data and the medication data, performing linear calculation to obtain drug absorption data. According to the scheme, by constructing the knowledge base containing the quantitative parameters and combining interval matching, function calculation and a priority weighting mechanism, the actual influence degree on the nutrients in a multi-drug scene can be accurately calculated, the problem of nutrient influence evaluation deviation caused by neglecting drug dose difference and multi-drug interaction in the prior art is solved, and the evaluation accuracy is improved. The actual influence coefficient of the medicine on various nutrients can be accurately quantified.

The application discloses a kind of based on blood data malignant tumor patient personalized nutrition assessment dynamic analysis method, it is related to personalized nutrition assessment technical field, including: with multilayer perception machine neural network as basic model, the data set S2 of blood routine and biochemical data is trained, obtain model_1;The historical blood routine and biochemical data of the person to be tested are added in data set S2 and constitute data set S3, and the weight of data set S3 is re-assigned;The model structure and parameter of model_1 are reloaded, the first layer parameter S3 of model_1 is fixed, the second layer and third layer parameter of model_1 are activated to continue training, and the training epoch is 200, obtain model_2.The application provides customized nutrition status assessment according to the data of each person's unique physiological change and treatment process, compared with general model, more can fit individual difference, and simultaneously, the ability of model is retrained by continuously incorporating new data, with the accumulation of patient historical data, the prediction accuracy and adaptability of model will be continuously improved.