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Conference Paper: Training, validation and testing of a multiscale three-dimensional deep learning algorithm in accurately diagnosing hepatocellular carcinoma on computed tomography. Oral Presentation (OS105)

TitleTraining, validation and testing of a multiscale three-dimensional deep learning algorithm in accurately diagnosing hepatocellular carcinoma on computed tomography. Oral Presentation (OS105)
Authors
Seto, WKWChiu, WHKLui, GZhou, CHENGCheng, HMWu, JShen, XPMak, LYHuang, JHLi, WKYuen, RMFYu, PLH
Issue Date2022
Citation
The International Liver Congress 2022, 22-26 June 2022. Journal of Hepatology, v. 77 n. S1, p. S78-79 How to Cite?
Persistent Identifierhttp://hdl.handle.net/10722/318195

 

DC FieldValueLanguage
dc.contributor.authorSeto, WKW-
dc.contributor.authorChiu, WHK-
dc.contributor.authorLui, G-
dc.contributor.authorZhou, CHENG-
dc.contributor.authorCheng, HM-
dc.contributor.authorWu, J-
dc.contributor.authorShen, XP-
dc.contributor.authorMak, LY-
dc.contributor.authorHuang, JH-
dc.contributor.authorLi, WK-
dc.contributor.authorYuen, RMF-
dc.contributor.authorYu, PLH-
dc.date.accessioned2022-10-07T10:34:24Z-
dc.date.available2022-10-07T10:34:24Z-
dc.date.issued2022-
dc.identifier.citationThe International Liver Congress 2022, 22-26 June 2022. Journal of Hepatology, v. 77 n. S1, p. S78-79-
dc.identifier.urihttp://hdl.handle.net/10722/318195-
dc.languageeng-
dc.relation.ispartofThe International Liver Congress 2022, 22-26 June 2022. Journal of Hepatology-
dc.titleTraining, validation and testing of a multiscale three-dimensional deep learning algorithm in accurately diagnosing hepatocellular carcinoma on computed tomography. Oral Presentation (OS105)-
dc.typeConference_Paper-
dc.identifier.emailSeto, WKW: wkseto@hku.hk-
dc.identifier.emailCheng, HM: hmcheng@hku.hk-
dc.identifier.emailMak, LY: lungyi@hku.hk-
dc.identifier.emailYuen, RMF: mfyuen@hku.hk-
dc.identifier.emailYu, PLH: plhyu@hku.hk-
dc.identifier.authoritySeto, WKW=rp01659-
dc.identifier.authorityChiu, WHK=rp02074-
dc.identifier.authorityMak, LY=rp02668-
dc.identifier.authorityYuen, RMF=rp00479-
dc.identifier.authorityYu, PLH=rp00835-
dc.identifier.hkuros337672-
dc.identifier.volume77-
dc.identifier.issueS1-
dc.identifier.spageS78-
dc.identifier.epage79-

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