Development and validation of explainable machine learning models for risk of mortality in transcatheter aortic valve implantation: TAVI risk machine scores

AIMS: Identification of high-risk patients and individualized decision support based on objective criteria for rapid discharge after transcatheter aortic valve implantation (TAVI) are key requirements in the context of contemporary TAVI treatment. This study aimed to predict 30-day mortality followi...

Descripción completa

Detalles Bibliográficos
Autores principales: Leha, Andreas, Huber, Cynthia, Friede, Tim, Bauer, Timm, Beckmann, Andreas, Bekeredjian, Raffi, Bleiziffer, Sabine, Herrmann, Eva, Möllmann, Helge, Walther, Thomas, Beyersdorf, Friedhelm, Hamm, Christian, Künzi, Arnaud, Windecker, Stephan, Stortecky, Stefan, Kutschka, Ingo, Hasenfuß, Gerd, Ensminger, Stephan, Frerker, Christian, Seidler, Tim
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/PMC10232286/
https://www.ncbi.nlm.nih.gov/pubmed/37265865
http://dx.doi.org/10.1093/ehjdh/ztad021

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232286/
https://www.ncbi.nlm.nih.gov/pubmed/37265865
http://dx.doi.org/10.1093/ehjdh/ztad021

Ejemplares similares