A preliminary study of the potential of tree classifiers in triage of high-grade squamous intraepithelial lesions

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dc.contributor.authorKarakitsos, P.en
dc.contributor.authorPouliakis, A.en
dc.contributor.authorMeristoudis, C.en
dc.contributor.authorMargari, N.en
dc.contributor.authorKassanos, D.en
dc.contributor.authorKyrgiou, M.en
dc.contributor.authorPanayiotides, J. G.en
dc.contributor.authorParaskevaidis, E.en
dc.date.accessioned2015-11-24T19:39:42Z
dc.date.available2015-11-24T19:39:42Z
dc.identifier.issn0884-6812-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/24268
dc.rightsDefault Licence-
dc.subject*Algorithmsen
dc.subjectCervical Intraepithelial Neoplasia/*diagnosis/etiology/pathologyen
dc.subjectEpithelial Cells/*pathologyen
dc.subjectFemaleen
dc.subjectHumansen
dc.subjectNeoplasms, Squamous Cell/*diagnosis/etiology/pathologyen
dc.subjectPapillomavirus Infections/complications/pathology/virologyen
dc.subjectUterine Cervical Neoplasms/*diagnosis/etiology/pathologyen
dc.titleA preliminary study of the potential of tree classifiers in triage of high-grade squamous intraepithelial lesionsen
heal.abstractOBJECTIVE: To investigate the potential value of tree classifiers for the triage of high-grade squamous intraepithelial lesions. STUDY DESIGN: The dataset comprised 808 histologically confirmed cases having a complete range of the cytologic sample assessments--liquid-based cytology, reflex human papillomavirus (HPV) DNA test, E6/E7 HPV mRNA test, and p16 immunocytochemical examinations. Data include 488 histologically negative (cervical intraepithelial neoplasia [CIN] 1 and below) or clinically negative cases and 320 with histologic diagnosis of CIN 2 or worse. Cytologic diagnosis was made according to the criteria of the Bethesda System. Cases were classified in two groups according to histology: those with CIN 2 or worse and those with CIN 1 and below. Fifty percent were randomly selected as a training set and the remaining were as a test set. RESULTS: Application of tree classifier on the test set gave correct classification of 66.9% for CIN 2 and above cases and 97.3% for CIN 1 and below, producing overall accuracy of 91.5%, outperforming cytologic diagnosis alone. CONCLUSION: Application of tree classifiers, based on standard cytologic diagnosis and expression of studied biomarkers, produces improved classification results for cervical precancerous lesions and cancer diagnosis anden
heal.accesscampus-
heal.fullTextAvailabilityTRUE-
heal.identifier.secondaryhttp://www.ncbi.nlm.nih.gov/pubmed/21980616-
heal.journalNameAnal Quant Cytol Histolen
heal.journalTypepeer-reviewed-
heal.languageen-
heal.publicationDate2011-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικήςel
heal.typejournalArticle-
heal.type.elΆρθρο Περιοδικούel
heal.type.enJournal articleen

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