Applying machine learning to predict bowel preparation adequacy in elderly patients for colonoscopy: development and validation of a web-based prediction tool.

Journal: Annals of medicine
PMID: 40065741

Abstract

BACKGROUND: Adequate bowel preparation is crucial for effective colonoscopy, especially in elderly patients who face a high risk of inadequate preparation. This study develops and validates a machine learning model to predict bowel preparation adequacy in elderly patients before colonoscopy.

Authors

  • Jianying Liu
    Trade union, Guilin Medical University, Guilin, China.
  • Wei Jiang
    Department of Civil Engineering, Johns Hopkins System Institute, Johns Hopkins University, Baltimore, Maryland.
  • Yahong Yu
    Department of Gastroenterology and Hepatology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China.
  • Jiali Gong
  • Guie Chen
    Department of Gastroenterology and Hepatology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China.
  • Yuxing Yang
    Department of Gastroenterology and Hepatology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China.
  • Chao Wang
    College of Agriculture, Shanxi Agricultural University, Taigu, Shanxi, China.
  • Dalong Sun
    Department of Gastroenterology and Hepatology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China.
  • Xuefeng Lu
    Department of Assisted Reproduction, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China.

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