Automated Machine Learning for the Early Prediction of the Severity of Acute Pancreatitis in Hospitals.

ABSTRACT:

Background

Machine learning (ML) algorithms are widely applied in building models of medicine due to their powerful studying and generalizing ability. This study aims to explore different ML models for early identification of severe acute pancreatitis (SAP) among patients hospitalized for acute pancreatitis.

Methods

This retrospective study enrolled patients with acute pancreatitis (AP) from multiple centers. Data from the First Affiliated Hospital and Changshu No. 1 Hospital of Soochow University were adopted for training and internal validation, and data from the Second Affiliated Hospital of Soochow University were adopted for external validation from January 2017 to December 2021. The diagnosis of AP and SAP was based on the 2012 revised Atlanta classification of acute p

SUBMITTER: Yin M 

PROVIDER: S-EPMC9226483 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature