Interpretable prediction of 30-day mortality in patients with acute pancreatitis based on machine learning and SHAP.

Journal: BMC medical informatics and decision making
PMID: 39501235

Abstract

BACKGROUND: Severe acute pancreatitis (SAP) can be fatal if left unrecognized and untreated. The purpose was to develop a machine learning (ML) model for predicting the 30-day all-cause mortality risk in SAP patients and to explain the most important predictors.

Authors

  • Xiaojing Li
    School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China.
  • Yueqin Tian
    Department of Rehabilitation Medicine, The Third Affiliated Hospital, Sun Yat-sen University, No. 600, Tianhe Road, Guangzhou, 510630, Guangdong, China.
  • Shuangmei Li
    Department of Emergency, the Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, 518033, China.
  • Haidong Wu
    Department of Emergency, the Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, 518033, China. wywhd@163.com.
  • Tong Wang
    School of Public Health, Shanxi Medical University, Taiyuan 030000, China; Key Laboratory of Coal Environmental Pathogenicity and Prevention (Shanxi Medical University), Ministry of Education, Taiyuan 030000, China.

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