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‐hos...

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Detalles Bibliográficos
Autores principales: Al'Aref, Subhi J., Singh, Gurpreet, van Rosendael, Alexander R., Kolli, Kranthi K., Ma, Xiaoyue, Maliakal, Gabriel, Pandey, Mohit, Lee, Bejamin C., Wang, Jing, Xu, Zhuoran, Zhang, Yiye, Min, James K., Wong, S. Chiu, Minutello, Robert M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6474922/
https://www.ncbi.nlm.nih.gov/pubmed/30834806
http://dx.doi.org/10.1161/JAHA.118.011160

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6474922/
https://www.ncbi.nlm.nih.gov/pubmed/30834806
http://dx.doi.org/10.1161/JAHA.118.011160

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