Individual-based treatment scheme recommendation system based on big data knowledge base

Abstract

The invention provides a treatment scheme recommendation system. The system comprises an information acquiring module, a matching module and a recommendation module. The information acquiring module is used for acquiring the illness state information and personal information of a user, the illness state information of the user serves as first illness state information, and the personal information of the user serves as first personal information. The matching module is used for matching the first illness state information and the first personal information with illness state information and personal information in a knowledge base and determining second illness state information matched with the first illness state information and second personal information matched with the first personal information. The recommendation module is used for acquiring a treatment scheme corresponding to the second illness state information and the second personal information and recommending the acquired treatment scheme to the user. Due to the fact that objective historical data of the illness state information and the personal information instead of personal subjective experience is depended on in the system, the recommended treatment scheme is higher in pertinence and reliability, and thus a doctor and a patient can be assisted in more quickly, more accurately and more reasonably determining the treatment scheme.

Description

technical field [0001] The invention relates to the fields of computer technology and medical and health technology, in particular to a personalized treatment plan recommendation system based on a big data knowledge base. Background technique [0002] At present, the traditional doctor-patient communication mode is that patients need to go to the hospital to find a doctor, and communicate with the doctor face to face. A treatment plan for the patient's condition is recommended to the patient. The above-mentioned method relies too much on the subjective experience and theoretical knowledge of experts or expert databases. At the same time, once the knowledge of experts or expert databases is wrong, it will produce wrong treatment plan recommendations, and the recommended plans will be biased. It has adverse effects and delays the timeliness for patients to obtain health. Contents of the invention [0003] Based on this, it is necessary to provide an accurate, effective and...

AI Technical Summary

Problems solved by technology

The above-mentioned method relies too much on the subjective experience and theoretical knowledge of experts or expert databases. At the same time, once the knowledge of experts or expert databases is wrong, it will produce wrong treatment plan recommendations, and the recommended plans will be biased. Has an adverse effect, delaying the timeliness of the patient's health

Images