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A multimodal deep learning model for cardiac resynchronisation therapy response prediction., , , , , , , и . Medical Image Anal., (2022)Uncertainty Aware Training to Improve Deep Learning Model Calibration for Classification of Cardiac MR Images., , , , , , , , , и 2 other автор(ы). CoRR, (2023)Assessing the ability of substrate mapping techniques to guide ventricular tachycardia ablation using computational modelling., , , , , , , , , и 4 other автор(ы). Comput. Biol. Medicine, (2021)The Effects of Non-ischemic Fibrosis Texture and Density on Mechanisms of Reentry., , , , , , , , , и . CinC, стр. 1-4. www.cinc.org, (2018)Uncertainty-Aware Training for Cardiac Resynchronisation Therapy Response Prediction., , , , , , , , , и 3 other автор(ы). STACOM@MICCAI, том 13131 из Lecture Notes in Computer Science, стр. 189-198. Springer, (2021)Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction., , , , , , , , , и 2 other автор(ы). MICCAI (1), том 12261 из Lecture Notes in Computer Science, стр. 284-293. Springer, (2020)Optimization of a Novel Activation-Repolarization Metric to Identify Targets for Catheter Ablation., , , , , , , , и . CinC, стр. 1-4. www.cinc.org, (2018)Uncertainty aware training to improve deep learning model calibration for classification of cardiac MR images., , , , , , , , , и 2 other автор(ы). Medical Image Anal., (августа 2023)Characterizing the clinical implementation of a novel activation-repolarization metric to identify targets for catheter ablation of ventricular tachycardias using computational models., , , , , , , , и . Comput. Biol. Medicine, (2019)Scar shape analysis and simulated electrical instabilities in a non-ischemic dilated cardiomyopathy patient cohort., , , , , , , , , и 1 other автор(ы). PLoS Comput. Biol., (2019)