Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study.

Journal: JMIR aging
PMID: 40305830

Abstract

BACKGROUND: Cognitive impairment, indicative of Alzheimer disease and other forms of dementia, significantly deteriorates the quality of life of older adult populations and imposes considerable burdens on families and health care systems worldwide. The early identification of individuals at risk for cognitive impairment through a convenient and rapid method is crucial for the timely implementation of interventions.

Authors

  • Hao Ren
    Department of Rheumatology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China. Electronic address: renhao67@aliyun.com.
  • Yiying Zheng
    The Affiliated Traditional Chinese Medicine Hospital, Guangzhou Medical University, Guangzhou, China.
  • Changjin Li
    Faculty of Data Science, City University of Macau, Taipa 999078, Macao SAR, China.
  • Fengshi Jing
    Institute for Healthcare Artificial Intelligence Application, Guangdong Second Provincial General Hospital, Guangzhou, China.
  • Qiting Wang
    School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China.
  • Zeyu Luo
    Chongqing Key Laboratory of Vector Insects.
  • Dongxiao Li
    Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore. elelc@nus.edu.sg.
  • Deyi Liang
    Guangdong Women and Children Hospital, Guangzhou, China.
  • Weiming Tang
    Dermatology Hospital of Southern Medical University, Guangzhou, China.
  • Li Liu
    Metanotitia Inc., Shenzhen, China.
  • Weibin Cheng
    Institute for Healthcare Artificial Intelligence Application, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, No. 466 Xingangzhong Road, Haizhu District, Guangzhou, 510317, China, 86 13929587059.

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