Development and External Validation of a Machine Learning-based Fall Prediction Model for Nursing Home Residents: A Prospective Cohort Study.

Journal: Journal of the American Medical Directors Association
PMID: 39067863

Abstract

OBJECTIVES: To develop and externally validate a machine learning-based fall prediction model for ambulatory nursing home residents. The focus is on predicting fall occurrences within 6 months after baseline assessment through a binary classification task, aiming to provide staff with an effective and user-friendly fall-risk assessment tool.

Authors

  • Lu Shao
    China University of Geosciences, Beijing, 100089, China.
  • Zhong Wang
    Department of Intensive Care Unit, The First Hospital of China Medical University, Shenyang, Liaoning, China.
  • Xiyan Xie
    Department of Nursing, Home for the Aged Guangzhou, Guangzhou, China.
  • Lu Xiao
    Department of Land Resources and Environment, School of Geography and Planning, Sun Yat-sen University, Guangzhou, China.
  • Ying Shi
    Laboratory of Neural Microcircuitry, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
  • Zhang-An Wang
    Department of Health Management, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
  • Jun-E Zhang
    School of Nursing, Sun Yat-sen University, Guangzhou, China. Electronic address: zhangje@mail.sysu.edu.cn.

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