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An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction, , , , , , , , , and 2 other author(s). The Lancet, 394 (10201): 861--867 (September 2019)Deep Neural Network for Cardiac Magnetic Resonance Image Segmentation., , , , , , , , , and 6 other author(s). J. Imaging, 8 (5): 149 (2022)Smart Wearables for Cardiac Monitoring - Real-World Use beyond Atrial Fibrillation., , , , , , , and . Sensors, 21 (7): 2539 (2021)Aggregating multiple real-world data sources using a patient-centered health-data-sharing platform., , , , , , , , , and 8 other author(s). npj Digit. Medicine, (2020)Computable Phenotypes to Identify Atrial Fibrillation from Electronic Medical Records., , , , , , , and . AMIA, AMIA, (2018)Feasibility of capturing real-world data from health information technology systems at multiple centers to assess cardiac ablation device outcomes: A fit-for-purpose informatics analysis report., , , , , , , , , and 5 other author(s). J. Am. Medical Informatics Assoc., 28 (10): 2241-2250 (2021)Automated extraction of sudden cardiac death risk factors in hypertrophic cardiomyopathy patients by natural language processing., , , , , , , , , and 3 other author(s). Int. J. Medical Informatics, (2019)Artificial intelligence-enabled ECG for left ventricular diastolic function and filling pressure., , , , , , , , , and 2 other author(s). npj Digit. Medicine, (2024)Mortality Prediction in Cardiac Intensive Care Unit Patients: A Systematic Review of Existing and Artificial Intelligence Augmented Approaches., , , and . Frontiers Artif. Intell., (2022)Leveraging Electronic Health Records for Identification of Features Associated with Sudden Death for Hypertrophic Cardiomyopathy Patients., , , , , , , , , and 1 other author(s). AMIA, AMIA, (2018)