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...

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Detalles Bibliográficos
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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2019
Materias:
Original Investigation
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

Internet

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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