Application Value of the Automated Machine Learning Model Based on Modified Computed Tomography Severity Index Combined With Serological Indicators in the Early Prediction of Severe Acute Pancreatitis.

Journal: Journal of clinical gastroenterology
Published Date: Aug 1, 2024

Abstract

BACKGROUND AND AIMS: Machine learning (ML) algorithms are widely applied in building models of medicine due to their powerful studying and generalizing ability. To assess the value of the Modified Computed Tomography Severity Index (MCTSI) combined with serological indicators for early prediction of severe acute pancreatitis (SAP) by automated ML (AutoML).

Authors

  • Rufa Zhang
    Department of Gastroenterology, Changshu Hospital Affiliated to Soochow University, Changshu No. 1 People's Hospital, Suzhou, Jiangsu 215500, China.
  • Minyue Yin
    Department of Gastroenterology, the First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China.
  • Anqi Jiang
    Department of Gastroenterology, Changshu Hospital Affiliated to Soochow University, Changshu No. 1 People's Hospital.
  • Shihou Zhang
    Department of Gastroenterology, Changshu Hospital Affiliated to Soochow University, Changshu No. 1 People's Hospital.
  • Luojie Liu
    Department of Gastroenterology, Changshu Hospital Affiliated to Soochow University, Suzhou, China.
  • Xiaodan Xu
    Department of Gastroenterology, Changshu Hospital Affiliated to Soochow University, First People's Hospital of Changshu City, No.1 Shuyuan Street, Changshu, Jiangsu, 215500, China. xuxiaodan20@126.com.

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