Early prediction of acute respiratory distress syndrome complicated by acute pancreatitis based on four machine learning models.

ABSTRACT:

Background

Acute Respiratory Distress syndrome (ARDS) is a common complication of Acute Pancreatitis (AP) and is associated with high mortality. This study used Machine Learning (ML) to predict ARDS in patients with AP at admission.

Methods

The authors retrospectively analyzed the data from patients with AP from January 2017 to August 2022. Clinical and laboratory parameters with significant differences between patients with and without ARDS were screened by univariate analysis. Then, Support Vector Machine (SVM), Ensembles of Decision Trees (EDTs), Bayesian Classifier (BC), and nomogram models were constructed and optimized after feature screening based on these parameters. Five-fold cross-validation was used to train each model. A test set was used to evaluate the predicti

SUBMITTER: Zhang M 

PROVIDER: S-EPMC10199163 | biostudies-literature | 2023 Jan-Dec

REPOSITORIES: biostudies-literature