Harnessing the Interplay between Genomics and Electrocardiograms using Artificial Intelligences MHIOMICS

Our project aims to improve heart health evaluation across diverse genetic backgrounds by integrating electrocardiograms (ECGs) with genomic data. We are developing an AI ECG framework trained on large biobanks to derive ECG representations and identify genetic factors shaping electrical traits across populations. We will test whether these AI derived features capture genetic risk relevant to atrial fibrillation and other cardiovascular disease, and evaluate robustness, calibration, and equity across age, sex, and genetic ancestry strata. External validation in an independent population cohort will quantify real world generalizability, supporting healthy ageing through improved risk stratification and prevention relevant insights.