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Using a Recurrent Neural Network To Inform the Use of Prostate-specific Antigen (PSA) and PSA Density for Dynamic Monitoring of the Risk of Prostate Cancer Progression on Active Surveillance

dc.contributor.authorSushentsev, N
dc.contributor.authorAbrego, L
dc.contributor.authorColarieti, A
dc.contributor.authorSanmugalingam, N
dc.contributor.authorStanzione, A
dc.contributor.authorZawaideh, JP
dc.contributor.authorCaglic, I
dc.contributor.authorZaikin, A
dc.contributor.authorBlyuss, O
dc.contributor.authorBarrett, T
dc.date.accessioned2023-10-17T12:51:08Z
dc.date.available2023-04-12
dc.date.available2023-10-17T12:51:08Z
dc.date.issued2023
dc.identifier.issn2666-1691
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/91354
dc.format.extent36 - 39
dc.relation.ispartofEUROPEAN UROLOGY OPEN SCIENCE
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subjectProstate canceren_US
dc.subjectActive surveillanceen_US
dc.subjectProstate -specific antigenen_US
dc.subjectPredictive modellingen_US
dc.subjectLongitudinal dataen_US
dc.subjectArtificial intelligenceen_US
dc.subjectRecurrent neural networksen_US
dc.titleUsing a Recurrent Neural Network To Inform the Use of Prostate-specific Antigen (PSA) and PSA Density for Dynamic Monitoring of the Risk of Prostate Cancer Progression on Active Surveillanceen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.euros.2023.04.002
pubs.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:001012200700001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6aen_US
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
pubs.volume52en_US


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Attribution 3.0 United States
Except where otherwise noted, this item's license is described as Attribution 3.0 United States