Geriatric depression and anxiety screening via deep learning using activity tracking and sleep data.

Journal: International journal of geriatric psychiatry
PMID:

Abstract

BACKGROUND: Geriatric depression and anxiety have been identified as mood disorders commonly associated with the onset of dementia. Currently, the diagnosis of geriatric depression and anxiety relies on self-reported assessments for primary screening purposes, which is uncomfortable for older adults and can be prone to misreporting. When a more precise diagnosis is needed, additional methods such as in-depth interviews or functional magnetic resonance imaging are used. However, these methods can not only be time-consuming and costly but also require systematic and cost-effective approaches.

Authors

  • Tae-Rim Lee
    Department of Artificial Intelligence, Sungkyunkwan University, Suwon, Korea.
  • Geon Ha Kim
    Department of Neurology, Ewha Womans University Mokdong Hospital, Ewha Womans University, College of Medicine, Seoul, South Korea.
  • Mun-Taek Choi
    School of Mechanical Engineering, Sungkyunkwan University, Republic of Korea. Electronic address: mtchoi@skku.edu.