Prediction of infected pancreatic necrosis in patients with acute necrotizing pancreatitis based on ensemble machine learning model.

ABSTRACT:

Background

To study the value of ensemble machine learning (EL) model in the prediction of infected pancreatic necrosis (IPN) among patients with acute necrotizing pancreatitis (ANP).

Methods

This study comprehensively analyzed 1073 acute necrotizing pancreatitis (ANP) patients admitted to Xiangya hospital from January 2011 to December 2023. The patients were divided into IPN group and sterile pancreatic necrosis (SPN) group based on IPN occurrence. All ANP patients were randomly divided into training dataset and validation dataset with a ratio of 7:3. The EL model was built by integrating multiple machine learning models (LASSO, random forest, and SVM). To verify the stability of the EL model, 78 ANP patients from the Third Xiangya hospital were included for external valida

SUBMITTER: Sun Z 

PROVIDER: S-EPMC12329969 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature