Fully Automated Cardiac Assessment for Diagnostic and Prognostic Stratification Following Myocardial Infarction.

ABSTRACT: Background Cardiovascular magnetic resonance imaging is considered the reference methodology for cardiac morphology and function but requires manual postprocessing. Whether novel artificial intelligence-based automated analyses deliver similar information for risk stratification is unknown. Therefore, this study aimed to investigate feasibility and prognostic implications of artificial intelligence-based, commercially available software analyses. Methods and Results Cardiovascular magnetic resonance data (n=1017 patients) from 2 myocardial infarction multicenter trials were included. Analyses of biventricular parameters including ejection fraction (EF) were manually and automatically assessed using conventional and artificial intelligence-based software. Obtained parameters entered regress

SUBMITTER: Schuster A 

PROVIDER: S-EPMC7726968 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature