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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...
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. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
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 |
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