Development and Validation of a Machine Learning Model Predicting Arteriovenous Fistula Failure in a Large Network of Dialysis Clinics

Background: Vascular access surveillance of dialysis patients is a challenging task for clinicians. We derived and validated an arteriovenous fistula failure model (AVF-FM) based on machine learning. Methods: The AVF-FM is an XG-Boost algorithm aimed at predicting AVF failure within three months amo...

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Detalles Bibliográficos
Autores principales: Peralta, Ricardo, Garbelli, Mario, Bellocchio, Francesco, Ponce, Pedro, Stuard, Stefano, Lodigiani, Maddalena, Fazendeiro Matos, João, Ribeiro, Raquel, Nikam, Milind, Botler, Max, Schumacher, Erik, Brancaccio, Diego, Neri, Luca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8656573/
https://www.ncbi.nlm.nih.gov/pubmed/34886080
http://dx.doi.org/10.3390/ijerph182312355

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8656573/
https://www.ncbi.nlm.nih.gov/pubmed/34886080
http://dx.doi.org/10.3390/ijerph182312355

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