The Price of Explainability in Machine Learning Models for 100-Day Readmission Prediction in Heart Failure: Retrospective, Comparative, Machine Learning Study

BACKGROUND: Sensitive and interpretable machine learning (ML) models can provide valuable assistance to clinicians in managing patients with heart failure (HF) at discharge by identifying individual factors associated with a high risk of readmission. In this cohort study, we delve into the factors d...

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Detalles Bibliográficos
Autores principales: Soliman, Amira, Agvall, Björn, Etminani, Kobra, Hamed, Omar, Lingman, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638630/
https://www.ncbi.nlm.nih.gov/pubmed/37889530
http://dx.doi.org/10.2196/46934

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638630/
https://www.ncbi.nlm.nih.gov/pubmed/37889530
http://dx.doi.org/10.2196/46934

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