An explainable AI framework for quantifying the stability of deep learning models analyzing ECG scans under controlled image perturbations.
A deep learning ensemble framework for detecting cardiac arrhythmias and predicting atrial fibrillation recurrence from ECG scans.
A genetic programming algorithm for building deep learning ensembles for ECG arrhythmia classification.
A deep learning approach for automated hepatocellular carcinoma analysis in multi-phase CT scans.
An InceptionV3-based approach for classifying ECG paper printouts using the Generalized Extreme Value activation function and loss weighting, developed as part of the George B. Moody PhysioNet Challenge 2024.
A deep learning approach for detecting brain metastases in longitudinal multi-modal MRI studies.