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Article: 5-Year progression prediction of endplate defects: Utilizing the EDPP-Flow convolutional neural network based on unbalanced data

Title5-Year progression prediction of endplate defects: Utilizing the EDPP-Flow convolutional neural network based on unbalanced data
Authors
Cheung, JPYKUANG, XZhang, TWang, KYang, C
Issue Date2023
Citation
Journal of Orthopaedics, 2023, v. 38, p. 7-13 How to Cite?
DOI: http://dx.doi.org/10.1016/j.jor.2023.03.001
Persistent Identifierhttp://hdl.handle.net/10722/326577
ISI Accession Number ID
WOS:000956316400001

 

DC FieldValueLanguage
dc.contributor.authorCheung, JPY-
dc.contributor.authorKUANG, X-
dc.contributor.authorZhang, T-
dc.contributor.authorWang, K-
dc.contributor.authorYang, C-
dc.date.accessioned2023-03-20T09:16:32Z-
dc.date.available2023-03-20T09:16:32Z-
dc.date.issued2023-
dc.identifier.citationJournal of Orthopaedics, 2023, v. 38, p. 7-13-
dc.identifier.urihttp://hdl.handle.net/10722/326577-
dc.languageeng-
dc.relation.ispartofJournal of Orthopaedics-
dc.title5-Year progression prediction of endplate defects: Utilizing the EDPP-Flow convolutional neural network based on unbalanced data-
dc.typeArticle-
dc.identifier.emailCheung, JPY: cheungjp@hku.hk-
dc.identifier.emailZhang, T: tgzhang@hku.hk-
dc.identifier.authorityCheung, JPY=rp01685-
dc.identifier.authorityZhang, T=rp02821-
dc.identifier.doi10.1016/j.jor.2023.03.001-
dc.identifier.hkuros344482-
dc.identifier.volume38-
dc.identifier.spage7-
dc.identifier.epage13-
dc.identifier.isiWOS:000956316400001-

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