Individual sub-health intervention method and system based on big data and artificial intelligence

Abstract

The invention discloses an individual sub-health nutrition and health intervention method based on big data and a management system. The method comprises the steps of establishing a sub-health assessment initial model and a nutrition and health intervention scheme library on the basis of evidence based medicine, epidemiology, dietary nutrition survey and nutrition intervention data; revising sub-health assessment model parameters by food, exercise and sign information analytic statistics results of a large sample of people and carrying out cross validation; acquiring individual sub-health score, an interpreted report and a recommended nutrition and health intervention scheme from personal information; in a process of executing the nutrition and health intervention scheme, assessing individual sub-health at regular intervals and adjusting the individual sub-health to obtain an optimal intervention effect; and meanwhile, continuously calculating and optimizing the individual sub-health assessment model by cumulative data of the personal information. The management system which executes the method consists of four modules including a personal information acquiring module, a calculating module, a display module and a supervision module. By the method and the management system, a scientific, individualized, visual and traceable sub-health solution is provided for residents, and long-term health records are established.

Description

technical field [0001] The invention relates to a sub-health intervention method and management system, in particular to a sub-health nutrition and health care intervention method and management system based on big data and artificial intelligence, and belongs to the field of health care technology. Background technique [0002] In recent years, with the advancement of life sciences, people's understanding of the process of life activities has become more and more in-depth, and correspondingly, the level of cognition and intervention technology for the occurrence and development of diseases has also been improved. With the development of evidence-based medicine and life sciences, people have achieved a lot of consensus on disease standards and disease types, making the disease a clear definition and classification standard, which is helpful for medical practitioners to choose appropriate means to intervene in diseases. It can delay the development of the disease or even rest...

AI Technical Summary

Problems solved by technology

[0003] In fact, at present, people’s understanding of their own disease or non-disease state (including healthy state and sub-health state) comes from regular medical institution physical examination reports. The main problems include: 1. The reference standard comes from the category of medical disease discrimination, which cannot evaluate the examinee The comprehensive health or sub-health state and degree can only judge whether it is in a disease state; 2. The physical examination often ignores the individual background differences of the examinee, such as diet, daily life, genetics, geography, age, etc. The difference in physiological state between individuals and groups close to the background, and thus determine the direction of improvement

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