Machine learning insights on activities of daily living disorders in Chinese older adults.

Journal: Experimental gerontology
PMID: 39603368

Abstract

OBJECTIVE: This study on the aged population in China first used a large-scale longitudinal survey database to explore how different life factors affect their ability to engage in daily activities. We select and integrate multiple machine models to obtain an excellent model for analyzing relationships. Based on the identified factors, our goal is to help them maintain a good daily life and quality of life.

Authors

  • Huanting Zhang
    HDU-ITMO Joint Institute, Hangzhou Dianzi University, Hangzhou 310018, China.
  • Wenhao Zhou
    The Molecular Genetic Diagnosis Center, Shanghai Key Lab of Birth Defect, Translational Medicine Research Center of Children Development and Diseases, Pediatrics Research Institute, Shanghai, China.
  • Jianan He
    College of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou 310018, China.
  • Xingyou Liu
    College of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou 310018, China.
  • Jie Shen
    Anhui Provincial Center for Drug Clinical Evaluation, Yijishan Hospital, Wannan Medical College, Wuhu, Anhui 241001, China; Pharmacy School, Wannan Medical College, Wuhu, Anhui 241002, China; Department of Clinical Pharmacy, Yijishan Hospital, Wannan Medical College, Wuhu, Anhui 241001, China; Anhui Provincial Engineering Research Center for Polysaccharides Drugs, Wannan Medical College, Wuhu, Anhui 241001, China.

Keywords

External Resources

Popular Topics
Recent Journals