Journal Articles by S. Raghunath

X. Zhang, A. E. U. Cerna, J. V. Stough, Y. Chen, B. J. Carry, A. Alsaid, S. Raghunath, D. P. vanMaanen, et al.
Generalizability and quality control of deep learning-based 2D echocardiography segmentation models in a large clinical dataset
The International Journal of Cardiovascular Imaging, 2022
S. Raghunath, J. M. Pfeifer, A. Ulloa, A. Nemani, T. Carbonati, L. Jing, D. P. vanMaanen, D. N. Hartzel, et al.
Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead Electrocardiogram and Help Identify Those at Risk of AF-Related Stroke
Circulation, 2021
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A. Ulloa, L. Jing, C. W. Good, S. Raghunath, J. D. Suever, C. D. Nevius, G. J. Wehner, D. N. Hartzel, et al.
Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality
Nature Biomedical Engineering, 2021
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A. E. Ulloa-Cerna, L. Jing, J. M. Pfeifer, S. Raghunath, J. A. Ruhl, D. B. Rocha, J. B. Leader, N. Zimmerman, et al.
rECHOmmend: an ECG-based machine-learning approach for identifying patients at high-risk of undiagnosed structural heart disease detectable by echocardiography
medRxiv, 2021
S. Raghunath, A. Ulloa, L. Jing, J. Stough, D. N. Hartzel, J. B. Leader, H. L. Kirchner, M. C. Stumpe, et al.
Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network
Nature medicine, 26(6), 2020
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