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Cited 15 time in webofscience Cited 8 time in scopus
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dc.contributor.authorKim, Y-
dc.contributor.authorPark, Y.H-
dc.contributor.authorLee, J.Y-
dc.contributor.authorChoi, I.Y-
dc.contributor.authorYu, H.-
dc.date.accessioned2017-07-19T12:46:20Z-
dc.date.available2017-07-19T12:46:20Z-
dc.date.created2016-08-16-
dc.date.issued2016-07-18-
dc.identifier.issn1472-6947-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/36415-
dc.description.abstractBackground: Prostate specific antigen (PSA) is an important biomarker to monitor the response to the treatment, but has not been fully utilized as a whole sequence. We used a longitudinal biomarker PSA to discover a new prognostic pattern that predicts castration-resistant prostate cancer (CRPC) after androgen deprivation therapy. Methods: We transformed the longitudinal PSA into a discrete sequence, used frequent sequential pattern mining to find candidate patterns from the sequences, and selected the most predictive and informative pattern among the candidates. Results: Patients were less likely to be CRPC if, after PSA values reach nadir, the PSA decreases more than 0.048 ng/ml during a month, and the decrease occurs again. This pattern significantly increased the accuracy of predicting CRPC by supplementing information provided by existing PSA patterns such as pretreatment PSA. Conclusions: This result can help clinicians to stratify men by the risk of CRPC and to determine the patient that needs intensive follow-up.-
dc.languageEnglish-
dc.publisherBioMed Central-
dc.relation.isPartOfBMC Medical Informatics and Decision Making-
dc.titleDiscovery of Prostate Specific Antigen Pattern to Predict Castration Resistant Prostate Cancer of Androgen Deprivation Therapy-
dc.typeArticle-
dc.identifier.doi10.1186/S12911-016-0297-0-
dc.type.rimsART-
dc.identifier.bibliographicCitationBMC Medical Informatics and Decision Making, v.16, no.SUPPL 1, pp.63-
dc.identifier.wosid000393278900005-
dc.date.tcdate2019-02-01-
dc.citation.numberSUPPL 1-
dc.citation.startPage63-
dc.citation.titleBMC Medical Informatics and Decision Making-
dc.citation.volume16-
dc.contributor.affiliatedAuthorYu, H.-
dc.identifier.scopusid2-s2.0-84978380790-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.wostc3-
dc.description.scptc3*
dc.date.scptcdate2018-05-121*
dc.description.isOpenAccessN-
dc.type.docTypeArticle; Proceedings Paper-
dc.subject.keywordPlusRECURRENCE-
dc.subject.keywordPlusSURVIVAL-
dc.subject.keywordPlusSTATISTICS-
dc.subject.keywordPlusTIME-
dc.subject.keywordAuthorProstate specific antigen-
dc.subject.keywordAuthorLongitudinal biomarker-
dc.subject.keywordAuthorFrequent sequential pattern mining-
dc.subject.keywordAuthorPrediction-
dc.relation.journalWebOfScienceCategoryMedical Informatics-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaMedical Informatics-

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유환조YU, HWANJO
Dept of Computer Science & Enginrg
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