A case for the use of deep learning algorithms for individual and population level assessments of mental health disorders: Predicting depression among China's elderly.

Journal: Journal of affective disorders
Published Date: Sep 24, 2024

Abstract

BACKGROUND: With the continuous advancement of age in China, attention should be paid to the mental well-being of the elderly population. The present study uses a novel machine learning (ML) method on a large representative elderly database in China as a sample to predict the risk factors of depression in the elderly population from both holistic and individual level.

Authors

  • Yingjie Wang
    Cardiovascular Department, Shuguang Hospital Affiliated to Shanghai University of TCM Shanghai, China.
  • Xuzhe Wang
    Nanjing University of Chinese Medicine, Nanjing, China.
  • Li Zhao
    International Initiative on Spatial Lifecourse Epidemiology (ISLE), the Netherlands; Department of Health Policy and Management, West China School of Public Health/West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, 610041, China; Research Center for Healthy City Development, Sichuan University, Chengdu, Sichuan, 610041, China; Healthy Food Evaluation Research Center, Sichuan University, Chengdu, Sichuan, 610041, China.
  • Kyle Jones
    School of Psychology, Swansea University, Swansea, UK. Electronic address: s.k.jones@swansea.ac.uk.

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