Performance of a Machine Learning Algorithm in Predicting Outcomes of Aortic Valve Replacement.

Journal: The Annals of thoracic surgery

Published Date: Feb 1, 2021

Abstract

BACKGROUND: This study evaluated the performance of a machine learning (ML) algorithm in predicting outcomes of surgical aortic valve replacement (SAVR).

Authors

Arman Kilic

Division of Cardiac Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania. Electronic address: kilica2@upmc.edu.
Anshul Goyal

Auton Lab, Carnegie Mellon University, Pittsburgh, Pennsylvania.
James K Miller

Auton Lab, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania.
Thomas G Gleason

Division of Cardiac Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania.
Artur Dubrawksi

Auton Lab, Carnegie Mellon University, Pittsburgh, Pennsylvania.

Keywords

Aged Algorithms Aortic Valve Aortic Valve Stenosis Education, Medical, Graduate Female Humans Machine Learning Male Prognosis ROC Curve Transcatheter Aortic Valve Replacement

External Resources

View on PubMed Access via DOI PubMed (32687831)

Performance of a Machine Learning Algorithm in Predicting Outcomes of Aortic Valve Replacement.

Abstract

Authors

Keywords

External Resources

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