Explainable Machine Learning for Atrial Fibrillation in the General Population Using a Generalized Additive Model　― A Cross-Sectional Study ―

Background: Atrial fibrillation (AF) is the most common arrhythmia and is associated with increased thromboembolic stroke risk and heart failure. Although various prediction models for AF risk have been developed using machine learning, their output cannot be accurately explained to doctors and pati...

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Detalles Bibliográficos
Autores principales: Kawakami, Masaki, Karashima, Shigehiro, Morita, Kento, Tada, Hayato, Okada, Hirofumi, Aono, Daisuke, Kometani, Mitsuhiro, Nomura, Akihiro, Demura, Masashi, Furukawa, Kenji, Yoneda, Takashi, Nambo, Hidetaka, Kawashiri, Masa-aki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Japanese Circulation Society 2021
Materias:
Original article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8811230/
https://www.ncbi.nlm.nih.gov/pubmed/35178483
http://dx.doi.org/10.1253/circrep.CR-21-0151

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8811230/
https://www.ncbi.nlm.nih.gov/pubmed/35178483
http://dx.doi.org/10.1253/circrep.CR-21-0151

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