Predicting target lesion failure following percutaneous coronary intervention through machine learning risk assessment models

AIMS: Central to the practice of precision medicine in percutaneous coronary intervention (PCI) is a risk-stratification tool to predict outcomes following the procedure. This study is intended to assess machine learning (ML)-based risk models to predict clinically relevant outcomes in PCI and to su...

Descripción completa

Detalles Bibliográficos
Autores principales: Mamas, Mamas A, Roffi, Marco, Fröbert, Ole, Chieffo, Alaide, Beneduce, Alessandro, Matetic, Andrija, Tonino, Pim A L, Paunovic, Dragica, Jacobs, Lotte, Debrus, Roxane, El Aissaoui, Jérémy, van Leeuwen, Frank, Kontopantelis, Evangelos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10689920/
https://www.ncbi.nlm.nih.gov/pubmed/38045434
http://dx.doi.org/10.1093/ehjdh/ztad051

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10689920/
https://www.ncbi.nlm.nih.gov/pubmed/38045434
http://dx.doi.org/10.1093/ehjdh/ztad051

Ejemplares similares