Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/13463
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dc.contributor.authorThanathornwong B.
dc.contributor.authorSuebnukarn S.
dc.contributor.authorOuivirach K.
dc.date.accessioned2021-04-05T03:24:04Z-
dc.date.available2021-04-05T03:24:04Z-
dc.date.issued2016
dc.identifier.issn1692607
dc.identifier.other2-s2.0-84958947637
dc.identifier.urihttps://ir.swu.ac.th/jspui/handle/123456789/13463-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84958947637&doi=10.1016%2fj.cmpb.2015.11.004&partnerID=40&md5=5000d9eaa7cc28c7bb811cc7d35e523c
dc.description.abstractTooth whitening is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach. However, the degree of color change after tooth whitening is known to vary substantially between studies. The present study aims to develop a clinical decision support system for predicting color change after in-office tooth whitening. We used the information from patients' data sets, and applied the multiple regression equation of CIELAB color coordinates including L*, a*, and b* of the original tooth color and the color difference (δE) that expresses the color change after tooth whitening. To evaluate the system performance, the patient's post-treatment color was used as "gold standard" to compare with the post-treatment color predicted by the system. There was a high degree of agreement between the patient's post-treatment color and the post-treatment color predicted by the system (kappa value = 0.894). The results obtained have demonstrated that the decision support system is possible to predict the color change obtained using an in-office whitening system using colorimetric values. © 2015 Elsevier Ireland Ltd.
dc.subjectArtificial intelligence
dc.subjectColor
dc.subjectDecision support systems
dc.subjectForecasting
dc.subjectPatient treatment
dc.subjectClinical decision support systems
dc.subjectColor changes
dc.subjectColor difference
dc.subjectGold standards
dc.subjectMultiple regression equations
dc.subjectMultiple regressions
dc.subjectPost treatment
dc.subjectTooth whitening
dc.subjectColorimetry
dc.subjectdecision support system
dc.subjectgold standard
dc.subjecthuman
dc.subjectmultiple regression
dc.subjecttooth
dc.subjecttooth color
dc.subjectclinical decision support system
dc.subjectcolor
dc.subjectdental procedure
dc.subjectColor
dc.subjectDecision Support Systems, Clinical
dc.subjectHumans
dc.subjectTooth Bleaching
dc.titleDecision support system for predicting color change after tooth whitening
dc.typeArticle
dc.rights.holderScopus
dc.identifier.bibliograpycitationComputer Methods and Programs in Biomedicine. Vol 125, (2016), p.88-93
dc.identifier.doi10.1016/j.cmpb.2015.11.004
Appears in Collections:Scopus 1983-2021

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