Risk stratification with explainable machine learning for 30-day procedure-related mortality and 30-day unplanned readmission in patients with peripheral arterial disease

Predicting 30-day procedure-related mortality risk and 30-day unplanned readmission in patients undergoing lower extremity endovascular interventions for peripheral artery disease (PAD) may assist in improving patient outcomes. Risk prediction of 30-day mortality can help clinicians identify treatme...

Descripción completa

Detalles Bibliográficos
Autores principales: Cox, Meredith, Panagides, J. C., Tabari, Azadeh, Kalva, Sanjeeva, Kalpathy-Cramer, Jayashree, Daye, Dania
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678279/
https://www.ncbi.nlm.nih.gov/pubmed/36409699
http://dx.doi.org/10.1371/journal.pone.0277507

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678279/
https://www.ncbi.nlm.nih.gov/pubmed/36409699
http://dx.doi.org/10.1371/journal.pone.0277507

Ejemplares similares