Individualized prediction of depressive disorder in the elderly: A multitask deep learning approach.

Journal: International journal of medical informatics
Published Date: Sep 23, 2019

Abstract

INTRODUCTION: Depressive disorder is one of the major public health problems among the elderly. An effective depression risk prediction model can provide insights on the disease progression and potentially inform timely targeted interventions. Therefore, research on predicting the onset of depressive disorder for elderly adults considering the sequential progression patterns is critically needed.

Authors

  • Zhongzhi Xu
    School of Public Health, Sun Yat-sen University, Guangzhou, China.
  • Qingpeng Zhang
    Department of Pharmacology and Pharmacy, The University of Hong Kong, Hong Kong, Hong Kong SAR, China.
  • Wentian Li
    Wuhan Hospital for Psychotherapy, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
  • Mingyang Li
    Department of Industrial and Management Systems Engineering, The University of South Florida, Tampa, FL, United States.
  • Paul Siu Fai Yip
    Centre for Suicide Research and Prevention and the Faculty of Social Sciences, The University of Hong Kong, Hong Kong, China.

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