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Comparison of Machine Learning Methods With National Cardiovascular Data Registry Models for Prediction of Risk of Bleeding After Percutaneous Coronary Intervention
IMPORTANCE: Better prediction of major bleeding after percutaneous coronary intervention (PCI) may improve clinical decisions aimed to reduce bleeding risk. Machine learning techniques, bolstered by better selection of variables, hold promise for enhancing prediction. OBJECTIVE: To determine whether...
Autores principales: | Mortazavi, Bobak J., Bucholz, Emily M., Desai, Nihar R., Huang, Chenxi, Curtis, Jeptha P., Masoudi, Frederick A., Shaw, Richard E., Negahban, Sahand N., Krumholz, Harlan M. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Association
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624806/ https://www.ncbi.nlm.nih.gov/pubmed/31290991 http://dx.doi.org/10.1001/jamanetworkopen.2019.6835 |
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