Chronic disease risk prediction method and system based on combination of artificial intelligence and medical experience

Abstract

The invention discloses a chronic disease risk prediction method and system based on combination of artificial intelligence and medical experience. The method comprises the steps of obtaining first input information; acquiring second input information; according to data requirements of the first input information and the second input information, extracting corresponding information from the medical institution and / or the physical examination institution / or the physical examination report to complete user information collection; performing data cleaning on the collected user information, and inputting the cleaned data into a pre-stored prediction model for processing to obtain a first risk value, the prediction model comprising a plurality of sub-prediction models; and performing secondary processing on the first risk value in combination with a questionnaire result to obtain a final risk prediction value. The method has the advantages that through organic combination of artificial intelligence and medical experience, a mechanism of joint decision making of a plurality of sub-prediction models is utilized, serious result deviation caused by the problem of model selection is avoided, and the situation of large model deviation caused by less training data is reduced.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a chronic disease risk prediction method and system using artificial intelligence combined with medical experience. Background technique [0002] It is very important to know and prevent diseases early. The ancient Chinese realized this truth very early. The genius doctor Bian Que said: "There is no disease when the doctor goes to the doctor, and the doctor wants to be sick when the doctor of Chinese medicine wants to be sick. The World Health Organization has proposed that 1 / 3 of cancers can be completely prevented, 1 / 3 of cancers can be cured through early detection, and 1 / 3 of cancers can use existing medical measures to prolong life, relieve pain, and improve quality of life. Let the public know and prevent early to reduce the probability of illness, so as to reduce the medical burden for the country and society. [0003] Artificial intelligence has been grad...

AI Technical Summary

Problems solved by technology

[0006] However, in the existing technology, most of the predictions are made through a single limited model, which is also prone to cause large prediction errors. At the same time, in the existing predictions, many external factors such as the environment, eating habits, and living habits are not considered. combined consideration

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