Valys, Alexander V.

Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram

Galloway, C. D., Valys, A. V., Shreibati, J. B., Treiman, D. L., Petterson, F. L., Gundotra, V. P., Albert, D. E., Attia, Z. I., Carter, R. E., Asirvatham, S. J., et al. (2019) · JAMA Cardiology

ECG Monitoring and AnalysisPotassium and Related Disorders

Cited by 318

Smartwatch Performance for the Detection and Quantification of Atrial Fibrillation

Wasserlauf, J., You, C., Patel, R., Valys, A., Albert, D., & Passman, R. (2019) · Circulation: Arrhythmia and Electrophysiology

ECG Monitoring and AnalysisNon-Invasive Vital Sign Monitoring

Cited by 245

NON-INVASIVE DETECTION OF HYPERKALEMIA WITH A SMARTPHONE ELECTROCARDIOGRAM AND ARTIFICIAL INTELLIGENCE

Galloway, C. D., Valys, A. V., Petterson, F. L., Gundotra, V. P., Treiman, D. L., Albert, D. E., Dillon, J. J., Attia, Z. I., & Friedman, P. A. (2018) · Journal of the American College of Cardiology

ECG Monitoring and AnalysisPotassium and Related Disorders

Cited by 17

PREDICTION OF THE HEART RATE CORRECTED QT INTERVAL (QTC) FROM A NOVEL, MULTILEAD SMARTPHONE-ENABLED ECG USING A DEEP NEURAL NETWORK

Schram, M., Shreibati, J. B., Bos, M., Galloway, C., Valys, A., Petterson, F., Gundotra, V., Albert, D., Attia, Z. I., Noseworthy, P., et al. (2019) · Journal of the American College of Cardiology

ECG Monitoring and AnalysisCardiac electrophysiology and arrhythmias

Cited by 6