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Predicting the amount of medical waste using kernel-based SVM and deep learning methods for a private hospital in Turkey

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dc.contributor.authorAltin, Fatma Gül
dc.contributor.authorBudak, İbrahim
dc.contributor.authorÖzcan, Fatma
dc.date.accessioned2026-01-04T18:47:53Z
dc.date.issued2023-06-01
dc.description.urihttps://doi.org/10.1016/j.scp.2023.101060
dc.identifier.doi10.1016/j.scp.2023.101060
dc.identifier.issn2352-5541
dc.identifier.openairedoi_________::2ffd8f849ef9d197474f3b2920f6479a
dc.identifier.orcid0000-0001-7762-6114
dc.identifier.scopus2-s2.0-85150444698
dc.identifier.startpage101060
dc.identifier.urihttps://hdl.handle.net/20.500.12597/40768
dc.identifier.volume33
dc.identifier.wos001043199700001
dc.language.isoeng
dc.publisherElsevier BV
dc.relation.ispartofSustainable Chemistry and Pharmacy
dc.rightsCLOSED
dc.titlePredicting the amount of medical waste using kernel-based SVM and deep learning methods for a private hospital in Turkey
dc.typeArticle
dspace.entity.typePublication
local.import.sourceOpenAire
local.indexed.atWOS
local.indexed.atScopus

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