rECHOmmend: an ECG-based machine learning approach for identifying patients at increased risk of undiagnosed structural heart disease detectable by echocardiography. Ulloa-Cerna, A. E, Jing, L., Pfeifer, J. M, Raghunath, S., Ruhl, J. A, Rocha, D. B, Leader, J. B, Zimmerman, N., Lee, G., Steinhubl, S. R, & others Circulation, 146(1):36–47, Lippincott Williams & Wilkins Hagerstown, MD, 2022. bibtex @article{ulloa2022rechommend,
title={rECHOmmend: an ECG-based machine learning approach for identifying patients at increased risk of undiagnosed structural heart disease detectable by echocardiography},
author={Ulloa-Cerna, Alvaro E and Jing, Linyuan and Pfeifer, John M and Raghunath, Sushravya and Ruhl, Jeffrey A and Rocha, Daniel B and Leader, Joseph B and Zimmerman, Noah and Lee, Greg and Steinhubl, Steven R and others},
journal={Circulation},
volume={146},
number={1},
pages={36--47},
year={2022},
publisher={Lippincott Williams \& Wilkins Hagerstown, MD}
}
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