Active health medical decision-making assisting method and equipment

Abstract

The invention relates to an active health medical decision-making assisting method and device. The method comprises the following steps: obtaining the individual features of a patient group with various health problems and diseases as a training sample, carrying out the training through a machine learning method or a deep learning method, and generating a disease risk assessment model corresponding to the health problems or diseases; pre-compiling health medical decision-making auxiliary schemes corresponding to various diseases, and storing the compiled health medical decision-making auxiliary schemes into a health medical decision-making auxiliary database; crawling individual data of the user from a multi-source heterogeneous health medical platform, and performing preprocessing and cleaning to obtain individual features of the user; inputting the individual characteristics of the user into a health assessment model, and outputting health problems or diseases that the user may suffer from; and obtaining a health medical decision-making auxiliary scheme corresponding to the health problem or disease from a health medical intervention database according to the disease that the user may suffer from, and sending the health medical decision-making auxiliary scheme to the user after cooperative processing by a doctor.

Description

technical field [0001] The invention relates to an active health medical decision-making assistant method and equipment, belonging to the technical fields of health medical care and data processing. Background technique [0002] At present, the specific manifestations of the medical models of major countries in the world are essentially the same, and they are still dominated by passive medical care. So far, this paternalistic medical model has lasted for thousands of years. Its characteristic is that patients blindly turn around doctors and operating entities, which is a passive consumption, and doctors also passively provide services, and the objects they serve are random and untargeted; information is asymmetric, and patients are in a state of passive consumption. Prevention is the most economical and effective health strategy, and the main health problems will be solved from the "source treatment". Health problems mainly include health prevention and treatment; due to li...

AI Technical Summary

Problems solved by technology

Health problems mainly include health prevention and treatment; due to limited medical resources, people cannot quickly understand their physical health status, and many diseases are often unaware of their health risks when they are in sub-health or embryonic states, and health prevention interventions are not taken; Usually, most major diseases are discovered and treated only in the middle and late stages, which greatly increases the difficulty and cost of treatment; patients with minor diseases or chronic diseases lack systematic guidance from doctors, and many patients basically let them develop without early intervention. It is passive intervention until it develops into...

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