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dc.contributor.authorLi, Xinyu
dc.contributor.authorvan Giessen, Anoukh
dc.contributor.authorAltunkaya, James
dc.contributor.authorSlieker, Roderick C
dc.contributor.authorBeulens, Joline W J
dc.contributor.author't Hart, Leen M
dc.contributor.authorPearson, Ewan R
dc.contributor.authorElders, Petra J M
dc.contributor.authorFeenstra, Talitha L
dc.contributor.authorLeal, Jose
dc.date.accessioned2023-05-09T09:20:55Z
dc.date.available2023-05-09T09:20:55Z
dc.date.issued2023-05-05
dc.identifier.pmid37146005
dc.identifier.doi10.2337/dc22-2170
dc.identifier.urihttp://hdl.handle.net/10029/626683
dc.language.isoenen_US
dc.rights© 2023 by the American Diabetes Association.
dc.titlePotential Value of Identifying Type 2 Diabetes Subgroups for Guiding Intensive Treatment: A Comparison of Novel Data-Driven Clustering With Risk-Driven Subgroups.en_US
dc.typeArticleen_US
dc.identifier.eissn1935-5548
dc.identifier.journalDiabetes Care 2023; 46(7):1395–1403en_US
dc.source.journaltitleDiabetes care
dc.source.countryUnited States


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