Please use this identifier to cite or link to this item: http://dspace.twc.edu.hk/jspui/handle/123456789/2137
DC FieldValueLanguage
dc.contributor.authorFuk-Hay Tang
dc.contributor.authorEva-Yi-Wah Cheung
dc.contributor.authorHiu-Lam Wong
dc.contributor.authorChun-Ming Yuen
dc.contributor.authorMan-Hei Yu
dc.contributor.authorPui-Ching Ho
dc.date.accessioned2023-01-05T07:20:08Z-
dc.date.available2023-01-05T07:20:08Z-
dc.date.issued2022-09
dc.identifier.citationLife (Basel), 12(9), 1380
dc.identifier.urihttp://dspace.twc.edu.hk/jspui/handle/123456789/2137-
dc.publisherLife (Basel)
dc.titleRadiomics from Various Tumour Volume Sizes for Prognosis Prediction of Head and Neck Squamous Cell Carcinoma: A Voted Ensemble Machine Learning Approach
item.fulltextNo Fulltext-
item.grantfulltextnone-
Appears in Collections:NUR Conference papers
Show simple item record

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.