The application of machine learning for identifying frailty in older patients during hospital admission.

Journal: BMC medical informatics and decision making
PMID: 39334179

Abstract

BACKGROUND: Early identification of frail patients and early interventional treatment can minimize the frailty-related medical burden. This study investigated the use of machine learning (ML) to detect frailty in hospitalized older adults with acute illnesses.

Authors

  • Yin-Yi Chou
    Center for Geriatrics & Gerontology, Taichung Veterans General Hospital, Taichung, Taiwan.
  • Min-Shian Wang
    Department of Critical Care Medicine, Taichung Veterans General Hospital, Taichung, Taiwan, ROC.
  • Cheng-Fu Lin
    Center for Geriatrics & Gerontology, Taichung Veterans General Hospital, Taichung, Taiwan.
  • Yu-Shan Lee
    Center for Geriatrics & Gerontology, Taichung Veterans General Hospital, Taichung, Taiwan.
  • Pei-Hua Lee
    Center for Geriatrics & Gerontology, Taichung Veterans General Hospital, Taichung, Taiwan.
  • Shih-Ming Huang
    Department of Pharmacy, Taichung Veterans General Hospital, Taichung, Taiwan.
  • Chieh-Liang Wu
    Center for Quality Management, Taichung Veterans General Hospital, Taichung, Taiwan.
  • Shih-Yi Lin
    Graduate Institute of Biomedical Sciences, China Medical University, Taichung.

Keywords

External Resources

Popular Topics
Recent Journals