Samuel J. Asirvatham

An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction

Zachi I. Attia, Peter A. Noseworthy, Francisco López-Jiménez et al. · The Lancet · 2019 · 1.4K citations

Artificial Intelligence, Electrophysiological Evaluation, Engineering +14

Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram

Zachi I. Attia, Suraj Kapa, Francisco López-Jiménez et al. · Nature Medicine · 2018 · 1.2K citations

Biomedical Artificial Intelligence, Electrophysiological Evaluation, Intelligent Diagnostics +11

Age and Sex Estimation Using Artificial Intelligence From Standard 12-Lead ECGs

Zachi I. Attia, Paul A. Friedman, Peter A. Noseworthy et al. · Circulation Arrhythmia and Electrophysiology · 2019 · 415 citations · Full text

Detection of Hypertrophic Cardiomyopathy Using a Convolutional Neural Network-Enabled Electrocardiogram

Wei-Yin Ko, Konstantinos C. Siontis, Zachi I. Attia et al. · Journal of the American College of Cardiology · 2020 · 379 citations

Cardiomyopathy, Electrophysiological Evaluation, Diagnosis +7

The Heart Rhythm Society (HRS)/American Society of Anesthesiologists (ASA) Expert Consensus Statement on the Perioperative Management of Patients with Implantable Defibrillators, Pacemakers and Arrhythmia Monitors: Facilities and Patient Management

George H. Crossley, Jeanne E. Poole, Marc A. Rozner et al. · Heart Rhythm · 2011 · 326 citations

Cardiac Anaesthesia, Cardiopulmonary Resuscitation, Device Therapy +15