Develop and validate machine learning models to predict the risk of depressive symptoms in older adults with cognitive impairment.

Journal: BMC psychiatry
PMID: 40069646

Abstract

BACKGROUND: Cognitive impairment and depressive symptoms are prevalent and closely interrelated mental health issues in the elderly. Traditional methods for identifying depressive symptoms in this population often lack effectiveness. Machine learning provides a promising alternative for developing predictive models that can facilitate early identification and intervention.

Authors

  • Enguang Li
    Department of Nursing, Jinzhou Medical University, Jinzhou, China.
  • Fangzhu Ai
    Department of Nursing, Jinzhou Medical University, Jinzhou, China.
  • Qingyan Tian
    Department of General Practice, Shenzhen Luohu People's Hospital(Luohu Clinical College of Shantou University Medical College), YouYi Road 47, Shenzhen, 518000, Guangdong, People's Republic of China.
  • Haocheng Yang
    Department of General Practice, Shenzhen Luohu People's Hospital(Luohu Clinical College of Shantou University Medical College), YouYi Road 47, Shenzhen, 518000, Guangdong, People's Republic of China.
  • Ping Tang
    Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing 100101, China. Electronic address: tangping@aircas.ac.cn.
  • Botang Guo
    Department of General Practice, Shenzhen Luohu People's Hospital(Luohu Clinical College of Shantou University Medical College), YouYi Road 47, Shenzhen, 518000, Guangdong, People's Republic of China. hmugbt@hrbmu.edu.cn.

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