Interpretable machine learning prediction of all-cause mortality

BACKGROUND: Unlike linear models which are traditionally used to study all-cause mortality, complex machine learning models can capture non-linear interrelations and provide opportunities to identify unexplored risk factors. Explainable artificial intelligence can improve prediction accuracy over li...

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Detalles Bibliográficos
Autores principales: Qiu, Wei, Chen, Hugh, Dincer, Ayse Berceste, Lundberg, Scott, Kaeberlein, Matt, Lee, Su-In
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530124/
https://www.ncbi.nlm.nih.gov/pubmed/36204043
http://dx.doi.org/10.1038/s43856-022-00180-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530124/
https://www.ncbi.nlm.nih.gov/pubmed/36204043
http://dx.doi.org/10.1038/s43856-022-00180-x

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