CardioVar: A Machine Learning Framework for Pathogenicity Prediction of Cardiomyopathy Genetic Variants

Abstract Motivation CardioVar is a machine learning framework developed to predict the pathogenicity of cardiomyopathy-associated genetic variants, providing a rapid and disease-focused classification score to support variant interpretation in cardiogenetic workflows. Results This approach supports variant interpretation within cardiac-related genes and may complement existing pan-disease models within a cardiomyopathy-specific context. In prospective case study settings, CardioVar demonstrated an 85% concordance with conventional tertiary analysis results. Availability https://github.com/nibrasissa/CardioVar Supplementary information Supplementary data are available at Bioinformatics online.