Identifying depression in the United States veterans using deep learning algorithms, NHANES 2005-2018.

Journal: BMC psychiatry
PMID: 37612646

Abstract

BACKGROUND: Depression is a common mental health problem among veterans, with high mortality. Despite the numerous conducted investigations, the prediction and identification of risk factors for depression are still severely limited. This study used a deep learning algorithm to identify depression in veterans and its factors associated with clinical manifestations.

Authors

  • Zihan Qu
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Yashan Wang
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Dingjie Guo
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Guangliang He
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Chuanying Sui
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Yuqing Duan
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Xin Zhang
    First Department of Infectious Diseases, The First Affiliated Hospital of China Medical University, Shenyang, China.
  • Linwei Lan
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Hengyu Meng
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Yajing Wang
    Department of Otolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
  • Xin Liu
    Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences, Weifang, Shandong, China.

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