Firouznia, M., Feeney, A., LaBarbera, M., McHale, M., Cantlay, C., Kalfas, N., Schoenhagen, P., Saliba, W., Tchou, P., Barnard, J., Chung, M., & Madabhushi, A.(2021).Machine Learning-Derived Fractal Features of Shape and Texture of the Left Atrium and Pulmonary Veins From Cardiac Computed Tomography Scans Are Associated With Risk of Recurrence of Atrial Fibrillation Postablation.Circulation: Arrhythmia and Electrophysiology,14(3),e009265.
Feeny, A., Rickard, J., Trulock, K., Patel, D., Toro, S., Moennich, L., Varma, N., Niebauer, M., Gorodeski, E., Grimm, R., Barnard, J., Madabhushi, A., & Chung, M.(2020).Machine Learning of 12-lead QRS Waveforms to Identify Cardiac Resynchronization Therapy Patients with Differential Outcomes.Circulation - Arrhythmia and Electrophysiology,13(7).
Feeny, A., Rickard, J., Patel, D., Toro, S., Trulock, K., Park, C., LaBarbera, M., Varma, N., Niebauer, M., Sinha, S., Gorodeski, E., Grimm, R., Ji, X., Barnard, J., Madabhushi, A., Spragg, D., & Chung, M.(2019).Machine Learning Prediction of Response to Cardiac Resynchronization Therapy: Improvement Versus Current Guidelines.Circulation - Arrhythmia and Electrophysiology,12(7).
