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postgraduate thesis: How can artificial neural network assist the prediction of the rehabilitation period in patients with fractured elbow, a preliminary experience in a local hospital database

TitleHow can artificial neural network assist the prediction of the rehabilitation period in patients with fractured elbow, a preliminary experience in a local hospital database
Authors
Fung, Wing Chiu馮穎釗
Issue Date2022
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Fung, W. C. [馮穎釗]. (2022). How can artificial neural network assist the prediction of the rehabilitation period in patients with fractured elbow, a preliminary experience in a local hospital database. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.
DegreeMaster of Medical Sciences
SubjectElbow - Fractures - Patients - Rehabilitation
Dept/ProgramOrthopaedics and Traumatology
Persistent Identifierhttp://hdl.handle.net/10722/317184

 

DC FieldValueLanguage
dc.contributor.authorFung, Wing Chiu-
dc.contributor.author馮穎釗-
dc.date.accessioned2022-10-03T07:25:52Z-
dc.date.available2022-10-03T07:25:52Z-
dc.date.issued2022-
dc.identifier.citationFung, W. C. [馮穎釗]. (2022). How can artificial neural network assist the prediction of the rehabilitation period in patients with fractured elbow, a preliminary experience in a local hospital database. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.-
dc.identifier.urihttp://hdl.handle.net/10722/317184-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subject.lcshElbow - Fractures - Patients - Rehabilitation-
dc.titleHow can artificial neural network assist the prediction of the rehabilitation period in patients with fractured elbow, a preliminary experience in a local hospital database-
dc.typePG_Thesis-
dc.description.thesisnameMaster of Medical Sciences-
dc.description.thesislevelMaster-
dc.description.thesisdisciplineOrthopaedics and Traumatology-
dc.description.naturepublished_or_final_version-
dc.date.hkucongregation2022-
dc.identifier.mmsid991044595508903414-

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