Supplementing Existing Societal Risk Models for Surgical Aortic Valve Replacement With Machine Learning for Improved Prediction

BACKGROUND: This study evaluated the role of supplementing Society of Thoracic Surgeons (STS) risk models for surgical aortic valve replacement with machine learning (ML). METHODS AND RESULTS: Adults undergoing isolated surgical aortic valve replacement in the STS National Database between 2007 and...

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Detalles Bibliográficos
Autores principales: Kilic, Arman, Habib, Robert H., Miller, James K., Shahian, David M., Dearani, Joseph A., Dubrawski, Artur W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8751954/
https://www.ncbi.nlm.nih.gov/pubmed/34658259
http://dx.doi.org/10.1161/JAHA.120.019697

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8751954/
https://www.ncbi.nlm.nih.gov/pubmed/34658259
http://dx.doi.org/10.1161/JAHA.120.019697

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