Prediction of Depression Index Based on LSTM and CNN
Year: 2024
Type: article
Abstract: In recent years, with the increase of social pressure and the acceleration of life pace, the incidence of depression has shown a rising trend, which makes the prevention, intervention and treatment of depression research is particularly important. At the same time, depression index is an important index used to measure and evaluate the degree of individual depression. In this paper, the MADRS scores corresponding to Montgomery Depression Scale were studied as depression index. In this paper, a depression index prediction model based on long short-term memory neural network (LSTM) and convolutional neural network (CNN) was established by collecting the data of several depressed patients in a hospital. The results show that the model has good predictive ability and stability, which can make a real-time judgment of depression in clinic and improve the efficiency of medical department.
DOI: 10.62051/7xyy5c33
Authors: Yi Li, Zida Cai, Jingyi Wang
Institution: Minzu University of China
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4401767689