File Download

There are no files associated with this item.

Supplementary

Conference Paper: An Artificial Intelligence Powered Platform for Auto-Analyses of Spine Alignment Irrespective of Image Quality with Prospective Validation

TitleAn Artificial Intelligence Powered Platform for Auto-Analyses of Spine Alignment Irrespective of Image Quality with Prospective Validation
Authors
Chu, KCheung, JPYZhang, T
Issue Date2022
Citation
International Society for the Study of the Lumbar Spine (ISSLS) Annual Meeting 2022, Boston, USA, 9-13 May 2022 How to Cite?
DescriptionZoom - Special Posters - no. ZSP6 (id#3014)
Persistent Identifierhttp://hdl.handle.net/10722/312964

 

DC FieldValueLanguage
dc.contributor.authorChu, K-
dc.contributor.authorCheung, JPY-
dc.contributor.authorZhang, T-
dc.date.accessioned2022-05-21T11:54:06Z-
dc.date.available2022-05-21T11:54:06Z-
dc.date.issued2022-
dc.identifier.citationInternational Society for the Study of the Lumbar Spine (ISSLS) Annual Meeting 2022, Boston, USA, 9-13 May 2022-
dc.identifier.urihttp://hdl.handle.net/10722/312964-
dc.descriptionZoom - Special Posters - no. ZSP6 (id#3014)-
dc.languageeng-
dc.relation.ispartof48th ISSLS Annual Meeting, 2022-
dc.titleAn Artificial Intelligence Powered Platform for Auto-Analyses of Spine Alignment Irrespective of Image Quality with Prospective Validation-
dc.typeConference_Paper-
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.hkuros333140-

Export via OAI-PMH Interface in XML Formats

OR

Export to Other Non-XML Formats