Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Tooth whitening is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach. Hover, the degree of color change after tooth whitening is known to vary substantially beten studies. The present study aims to develop a clinical decision support system for predicting color change after in-office tooth whitening.  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 beten 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.
['Bhornsawan Thanathornwong', 'Siriwan Suebnukarn', 'Kan Ouivirach']
I am writing a research paper on a idea Decision support system for predicting color change after tooth whitening
[{"from": "human", "value": "I am writing a research paper on a idea Decision support system for predicting color change after tooth whitening"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Tooth whitening is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach. Hover, the degree of color change after tooth whitening is known to vary substantially beten studies. The present study aims to develop a clinical decision support system for predicting color change after in-office tooth whitening.  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 (\u0394E) 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 beten 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."}]