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
Subjects:
Deep Learning
(MeSH)
Perioperative Cardiac Risk Assessment and Management
(OpenAlex Topic)
Optimization of Perioperative Fluid Therapy
(OpenAlex Topic)
Advanced Cardiac Imaging Techniques and Diagnostics
(OpenAlex Topic)
Publication Type:
Article
Unique ID:
10.1016/s2589-7500(23)00220-0
PMID:
Journal:
Publication Date:
Data Source:
OpenAlex
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