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Machine learning for improved pathological staging of prostate cancer : A performance comparison on a range of classifiers

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dc.contributor.authorRegnier-Coudert, Olivier
dc.contributor.authorMcCall, John
dc.contributor.authorLothian, Robert
dc.contributor.authorLam, Thomas
dc.contributor.authorMcClinton, Sam
dc.contributor.authorN'Dow, James
dc.contributor.institutionUniversity of Aberdeen.Natural & Computing Sciencesen
dc.contributor.institutionUniversity of Aberdeen.Other Applied Health Sciencesen
dc.contributor.institutionUniversity of Aberdeen.Academic Urology Uniten
dc.contributor.institutionUniversity of Aberdeen.Institute of Applied Health Sciencesen
dc.date.accessioned2012-05-07T13:39:01Z
dc.date.available2012-05-07T13:39:01Z
dc.date.issued2012-05
dc.description.statusPeer revieweden
dc.format.extent11
dc.format.extent1681207
dc.identifier12300529
dc.identifier6b62f20e-38fb-44f2-845a-27fa7b252a8b
dc.identifier84858859611
dc.identifier.citationRegnier-Coudert, O, McCall, J, Lothian, R, Lam, T, McClinton, S & N'Dow, J 2012, 'Machine learning for improved pathological staging of prostate cancer : A performance comparison on a range of classifiers', Artificial Intelligence in Medicine, vol. 55, no. 1, pp. 25-35. https://doi.org/10.1016/j.artmed.2011.11.003en
dc.identifier.doi10.1016/j.artmed.2011.11.003
dc.identifier.iss1en
dc.identifier.issn0933-3657
dc.identifier.otherORCID: /0000-0001-5340-0081/work/162725330
dc.identifier.urihttp://hdl.handle.net/2164/2417
dc.identifier.vol55en
dc.language.isoeng
dc.relation.ispartofArtificial Intelligence in Medicineen
dc.subjectSDG 3 - Good Health and Well-beingen
dc.subjectpredictive modellingen
dc.subjectbayesian networksen
dc.subjectlogistic regressionen
dc.subjectprostate cancer stagingen
dc.subjectpartin tablesen
dc.subjectRC0254 Neoplasms. Tumors. Oncology (including Cancer)en
dc.subject.lccRC0254en
dc.titleMachine learning for improved pathological staging of prostate cancer : A performance comparison on a range of classifiersen
dc.typeJournal articleen

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