Explainable artificial intelligence for predicting cardiovascular events in hospitalised COVID-19 patients.

ABSTRACT:

Introduction

Coronavirus disease (COVID-19) increases the risk of cardiovascular complications, and artificial intelligence (AI) offers promising tools for early risk prediction.

Objective

To develop AI models capable of identifying predictors of cardiovascular events in hospitalized COVID-19 patients.

Methodology

Retrospective multicentre cohort, which included adult COVID-19 patients from 25 hospitals (March/2021-August/2022). Cardiovascular outcomes, inluding arrhythmia, acute heart failure, myocardial infarction, myocarditis, and pericarditis, were combined into a composite outcome. Two predictive models were developed using the Light gradient-boosting machine (LightGBM): model 1 used 59 variables (demographic, clinical, laboratory, and socioeconomic data) while m

SUBMITTER: Marcolino MS 

PROVIDER: S-EPMC12613670 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature