Accurate prediction of acute pancreatitis severity with integrative blood molecular measurements.

Journal: Aging
Published Date: Mar 10, 2021

Abstract

BACKGROUND: Early diagnosis of severe acute pancreatitis (SAP) is essential to minimize its mortality and improve prognosis. We aimed to develop an accurate and applicable machine learning predictive model based on routine clinical testing results for stratifying acute pancreatitis (AP) severity.

Authors

  • Hong-Wei Sun
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China.
  • Jing-Yi Lu
    Singlera Genomics Inc., San Diego, CA 92037, USA.
  • Yi-Xin Weng
    Key Laboratory of Intelligent Critical Care and Life Support Research of Zhejiang Province, Department of Intensive Care, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China.
  • Hao Chen
    The First School of Medicine, Wenzhou Medical University, Wenzhou, China.
  • Qi-Ye He
    Singlera Genomics Inc., San Diego, CA 92037, USA.
  • Rui Liu
    School of Education, China West Normal University, Nanchong, Sichuan, China.
  • Hui-Ping Li
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China.
  • Jing-Ye Pan
    Key Laboratory of Intelligent Critical Care and Life Support Research of Zhejiang Province, Department of Intensive Care, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China.
  • Ke-Qing Shi
    Translational Medicine Laboratory, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China.

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