Interpretable machine learning for mortality modeling on patients with chronic diseases considering the COVID-19 pandemic in a region of Chile: A Shapley value based approach

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dc.contributor.author	Barría Sandoval, Claudia
dc.contributor.author	Ferreira, Guillermo
dc.contributor.author	Venegas, Maritza Espinoza
dc.contributor.author	Marchant, Vicente
dc.date.accessioned	2024-09-12T03:43:27Z
dc.date.available	2024-09-12T03:43:27Z
dc.date.issued	2023-04-25
dc.identifier.issn	2768-4520
dc.identifier.uri	https://repositorio.uss.cl/handle/uss/11669
dc.language.iso	eng
dc.relation.ispartof	vol. 1 Issue: no. 1 Pages:
dc.source	Research in Statistics
dc.title	Interpretable machine learning for mortality modeling on patients with chronic diseases considering the COVID-19 pandemic in a region of Chile: A Shapley value based approach	en
dc.type	Artículo
dc.publisher.department	Facultad de Ciencias para el Cuidado de la Salud

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