Interpretable generalized neural additive models for mortality prediction of COVID-19 hospitalized patients in Hamadan, Iran

BACKGROUND: The high number of COVID-19 deaths is a serious threat to the world. Demographic and clinical biomarkers are significantly associated with the mortality risk of this disease. This study aimed to implement Generalized Neural Additive Model (GNAM) as an interpretable machine learning metho...

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Detalles Bibliográficos
Autores principales: Moslehi, Samad, Mahjub, Hossein, Farhadian, Maryam, Soltanian, Ali Reza, Mamani, Mojgan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9803600/
https://www.ncbi.nlm.nih.gov/pubmed/36585627
http://dx.doi.org/10.1186/s12874-022-01827-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9803600/
https://www.ncbi.nlm.nih.gov/pubmed/36585627
http://dx.doi.org/10.1186/s12874-022-01827-y

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