Constructing a fall risk prediction model for hospitalized patients using machine learning.

Journal: BMC public health
PMID: 39833780

Abstract

STUDY OBJECTIVES: This study aimed to identify the risk factors associated with falls in hospitalized patients, develop a predictive risk model using machine learning algorithms, and evaluate the validity of the model's predictions.

Authors

  • Cheng-Wei Kang
    West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, China. kangarooqq@163.com.
  • Zhao-Kui Yan
    Department of Orthopaedics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, 610041, China.
  • Jia-Liang Tian
    Department of Orthopaedics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, 610041, China.
  • Xiao-Bing Pu
    Department of Orthopaedics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, 610041, China.
  • Li-Xue Wu
    Department of Pathology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, 610041, China. wulixuescu@163.com.

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