Machine learning using institution-specific multi-modal electronic health records improves mortality risk prediction for cardiac surgery patientsCentral MessagePerspective

Machine learning using institution-specific multi-modal electronic health records improves mortality risk prediction for cardiac surgery patientsCentral MessagePerspective

Background: The Society of Thoracic Surgeons risk scores are widely used to assess risk of morbidity and mortality in specific cardiac surgeries but may not perform optimally in all patients. In a cohort of patients undergoing cardiac surgery, we developed a data-driven, institution-specific machine...

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Bibliographic Details
Main Authors: Aaron J. Weiss, MD, PhD, Arjun S. Yadaw, PhD, David L. Meretzky, MA, Matthew A. Levin, MD, David H. Adams, MD, Ken McCardle, MS, Gaurav Pandey, PhD, Ravi Iyengar, PhD
Format: Article
Language:English
Published: Elsevier 2023-06-01
Series:JTCVS Open
Subjects:
cardiac surgery
clinical outcomes
electronic health records
machine learning
prediction modeling
risk prediction
Online Access:http://www.sciencedirect.com/science/article/pii/S2666273623000852

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http://www.sciencedirect.com/science/article/pii/S2666273623000852

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