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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2022
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| Materias: | |
| 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 |