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Correction: Accurate, automated classifcation of radiographic knee osteoarthritis severity using a novel method of deep learning: Plug-in modules

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dc.contributor.authorLee, Do Weon-
dc.contributor.authorSong, Dae Seok-
dc.contributor.authorHan, Hyuk-Soo-
dc.contributor.authorRo, Du Hyun-
dc.date.accessioned2025-05-13T05:30:18Z-
dc.date.available2025-05-13T05:30:18Z-
dc.date.issued2025-04-
dc.identifier.issn2234-0726-
dc.identifier.issn2234-2451-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/58327-
dc.description.abstractFollowing publication of the original article [1], we have been notified that body text contained incorrectly published parts. The original text was as follows: The accuracy was the lowest for KL grade 1 (46%) and the highest for KL grade 4 (93%). Table 2 Sensitivity and specificity of the proposed model for each Kellgren–Lawrence grade This has been corrected to: The accuracy was the lowest for KL grade 1 (43%) and the highest for KL grade 4 (96%). Sensitivity and specificity of the proposed model for each Kellgren–Lawrence grade The original article was updated. © The Author(s) 2025.-
dc.language영어-
dc.language.isoENG-
dc.publisher대한슬관절학회-
dc.titleCorrection: Accurate, automated classifcation of radiographic knee osteoarthritis severity using a novel method of deep learning: Plug-in modules-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.doi10.1186/s43019-025-00268-3-
dc.identifier.scopusid2-s2.0-105004348321-
dc.identifier.wosid001479119600001-
dc.identifier.bibliographicCitationKnee Surgery & Related Research, v.37, no.1-
dc.citation.titleKnee Surgery & Related Research-
dc.citation.volume37-
dc.citation.number1-
dc.type.docTypeCorrection-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClassesci-
dc.description.journalRegisteredClasskci-
dc.relation.journalResearchAreaOrthopedics-
dc.relation.journalResearchAreaSurgery-
dc.relation.journalWebOfScienceCategoryOrthopedics-
dc.relation.journalWebOfScienceCategorySurgery-
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