Decision support system for predicting color change after tooth whitening. Issue 125 (March 2016)

• Record Type: Journal Article
• Authors: Thanathornwong, Bhornsawan; Suebnukarn, Siriwan; Ouivirach, Kan
• Is Part Of: Computer methods and programs in biomedicine. Issue 125(2016)
• Page Start: 88
• Page End: 93
• Publication Date: 2016-03
• Subjects: Tooth whitening -- Decision support system -- Multiple regression; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2015.11.004
• Languages: English
• ISSNs: 0169-2607

Abstract

Abstract: Tooth 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 (Δ E ) 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.