DH-575-04 ARRHYTHMIC SUDDEN DEATH (SCDA) SURVIVAL PREDICTION USING DEEP LEARNING (DL) ANALYSIS OF CONTRAST-ENHANCED CARDIAC MAGNETIC RESONANCE IMAGING (LGE-CMR)

Abstract

Current approaches to SCDA risk prediction represent broad guidelines and fail to incorporate personalized, complex, large-scale clinical data and individualized phenotyping. DL approaches are ideal for such data, however, most of the DL work related to arrhythmia has focused on disease classification and detection from ECG time series data. Furthermore, mechanistically, ventricular arrhythmia in patients with structural heart disease often results from the heterogeneous scar distribution, however, DL on raw imaging scans has not been explored for risk analysis.