Early warning method and device for cognitive and behavioral disorders, equipment and storage medium

Abstract

The invention relates to the field of medical treatment, and discloses a cognitive and behavioral disorder early warning method, device and equipment and a storage medium, and the method comprises the steps: obtaining the basic information of a detected object, inputting the basic information into a graph neural network, and obtaining a first prediction probability H1; receiving a biological signal uploaded by a monitoring bracelet of a measured object, and inputting the biological signal to the XGboost model to obtain a second prediction probability H2; receiving daily monitoring data uploaded by the monitoring bracelet, and inputting the daily monitoring data to the RNN model to obtain a third prediction probability H3; performing weighted calculation on the H1, the H2 and the H3 based on a preset weighting algorithm to obtain a disease probability H4 of the detected object; and if the H4 is higher than the preset probability threshold, generating an early warning signal, and sending the early warning signal to a preset port. Aiming at the technical problem that the disease and disease development of a patient cannot be monitored in real time at present, the method aims at finding the disease in advance, monitoring the specific physiological condition of the patient in real time in daily life, improving the diagnosis efficiency and realizing uninterrupted monitoring measures.

Description

technical field [0001] The invention relates to the medical field, in particular to an early warning method, device, equipment and storage medium for cognitive and behavioral disorders. Background technique [0002] Alzheimer's disease (AD) is a major disease facing human society and has become a serious public health problem. At present, there are more than 100 million dementia patients in China; with the development of artificial intelligence, various artificial intelligence technologies have been applied to Alzheimer's disease Giants such as Nvidia, Tencent, and Apple are all carrying out related research in the field of Alzheimer's. Artificial intelligence can effectively identify the degree of illness of patients by extracting and analyzing data from patients' medical images, daily audio, questionnaires, and biosignal feedback. Accurately realizing the early diagnosis of Alzheimer's disease can help patients to carry out targeted treatment, slow down the exacerbation o...

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to solve the technical problem of being unable to monitor the patient's disease and disease progression in real time in the existing early warning methods for cognitive and behavioral disorders

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