A health recommendation system and recommendation method based on medical knowledge graph

Abstract

This application provides a health recommendation system based on medical knowledge graphs, including an abnormal sign database; the abnormal sign database includes medical abnormal data and period abnormal data; user health portraits can be established through medical abnormal data and period abnormal data. The present application also provides a health recommendation method, including: obtaining the abnormal category characteristic label of user a; obtaining the occurrence time of the i-th abnormal category characteristic label AXi, setting the associated time period of the i-type abnormal category characteristic label AXi as △ATi, Each associated time period of AXi includes each occurrence time of AXi; obtain the abnormal category feature AF that occurs in all associated time periods of the abnormal category feature AXi; combine all abnormal categories that occur within the associated time period △ATi of the abnormal category feature AXi Feature AF is recorded as AXi's preset associated feature, and a user's health profile is constructed based on the associated abnormal category features. This application provides an optimized health recommendation system.

Description

technical field [0001] This application relates to the field of user health portraits, in particular to a health recommendation system and recommendation method based on medical knowledge graphs. Background technique [0002] With the continuous development of today's economy, the aging of the social population is becoming more and more serious, and senile diseases are prevalent. At the same time, the greater life pressure is gradually breeding young and middle-aged people to suffer from chronic diseases. In order to facilitate the statistics of users, abnormal signs and symptoms and tracking, now In the existing technology, a personal health record report for each user has been gradually formed and information sharing is realized through the Internet and big data; however, most of the data in the existing personal health record report only involves the physical parameters of the patient's support, and has no impact on the patient's daily life. Abnormal data, living conditio...

AI Technical Summary

Problems solved by technology

[0002] With the continuous development of today's economy, the aging of the social population is becoming more and more serious, and senile diseases are prevalent. At the same time, the greater life pressure is gradually breeding young and middle-aged people to suffer from chronic diseases. In order to facilitate the statistics of users, abnormal signs and symptoms and tracking, now In the existing technology, a personal health record report for each user has been gradually formed and information sharing is realized through the Internet and big data; however, most of the data in the existing personal health record report only involves the physical parameters of the patient's support, and has no impact on the patient's daily life. Abnormal data, living conditions, work, diet, exercise and other information found in the system are rarely obtained and updated in a timely manner, and it is impossible to perform multi-dimensional and all-round real-time portraits of users, so that the multi-dimensional information of patients and users cannot be obtained in a timely manner because they cannot form Effective treatment and health care measures affect the timely reminder and effectiveness of the user's treatment; the evaluation and prediction of the user's health status in the prior art is often based on the standard physical characteristics of the same type of patient users, rather than the current user's Standard physical characteristics are used as a reference, so it is not possible to effectively propose the most suitable guidance and intervention measures for current users and patients, and the needs of individuals, enterprises and health supervision units cannot be met

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