Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study

Ouyang, D., Theurer, J., Stein, N. R., Hughes, J. W., Elias, P., He, B., Yuan, N., Duffy, G., Sandhu, R. K., Ebinger, J., Botting, P., Jujjavarapu, M., Claggett, B., Tooley, J. E., Poterucha, T., Chen, J. H., Nurok, M., Perez, M., Perotte, A., … Albert, C. M. (2024). Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study. The Lancet Digital Health, 6(1), e70–e78. https://doi.org/10.1016/s2589-7500(23)00220-0
Authors:
David Ouyang
John Theurer
Nathan R. Stein
J. Weston Hughes
Pierre Elias
Bryan He
Neal Yuan
Grant Duffy
Roopinder K. Sandhu
Joseph E. Ebinger
Patrick Botting
Melvin Jujjavarapu
Brian Claggett
James Tooley
Tim Poterucha
Jonathan Chen
Michael Nurok
Marco Perez
Adler Perotte
James Zou
Nancy R. Cook
Sumeet S. Chugh
Susan Cheng
Christine M. Albert
Affiliated Authors:
Pierre Elias
Tim Poterucha
Adler Perotte
Publication Type:
Article
Unique ID:
10.1016/s2589-7500(23)00220-0
PMID:
Publication Date:
Data Source:
OpenAlex

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