Determinants of In‐Hospital Mortality After Percutaneous Coronary Intervention: A Machine Learning Approach

Determinants of In‐Hospital Mortality After Percutaneous Coronary Intervention: A Machine Learning Approach

Background The ability to accurately predict the occurrence of in‐hospital death after percutaneous coronary intervention is important for clinical decision‐making. We sought to utilize the New York Percutaneous Coronary Intervention Reporting System in order to elucidate the determinants of in‐hosp...

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Bibliographic Details
Main Authors: Subhi J. Al'Aref, Gurpreet Singh, Alexander R. van Rosendael, Kranthi K. Kolli, Xiaoyue Ma, Gabriel Maliakal, Mohit Pandey, Bejamin C. Lee, Jing Wang, Zhuoran Xu, Yiye Zhang, James K. Min, S. Chiu Wong, Robert M. Minutello
Format: Article
Language:English
Published: Wiley 2019-03-01
Series:Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
Subjects:
big data analytics
in‐hospital mortality
machine learning
percutaneous coronary intervention
Online Access:https://www.ahajournals.org/doi/10.1161/JAHA.118.011160

Internet

https://www.ahajournals.org/doi/10.1161/JAHA.118.011160

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