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Comparative agreement among traditional, digital, and experimental AI-based shade selection methods in dentistry: A
Mehmet Ünal1, Selin Polatoğlu2
1Assistant Professor, Department of Prosthetic Dentistry, Faculty of Dentistry, Karamanoğlu Mehmetbey University, Karaman, Turkey.
The Journal of Prosthetic Dentistry
|December 23, 2025
Summary
Digital dental shade selection methods show poor agreement. This study found low consistency between traditional, digital, and AI-assisted tools, indicating a need for complementary approaches in shade matching.
Area of Science:
- Dental materials science
- Digital dentistry
- Clinical diagnostics
Background:
- Shade selection in dentistry is traditionally subjective.
- Digital tools offer potential for objective and consistent shade matching.
- Lack of consensus exists regarding the agreement and consistency of various digital shade selection methods.
Purpose of the Study:
- To evaluate the agreement among traditional, digital, and AI-assisted shade selection methods.
- To compare the consistency of different shade selection techniques in a clinical setting.
Main Methods:
- 85 participants underwent shade analysis on the maxillary central incisor.
- Four methods were used: traditional (TM), spectrophotometer (S), intraoral scanner (IOS), and AI (ChatGPT-4).
- Cohen and Fleiss kappa methods analyzed agreement between and among methods.
Main Results:
- Moderate agreement was observed between traditional and intraoral scanner methods (kappa=.421).
- Low agreement was found between traditional and AI methods (kappa=.064).
- A slight but significant agreement was found among all four methods (Fleiss kappa=.071).
Conclusions:
- Dental shade selection methods exhibit very low agreement.
- Digitalization is transforming shade selection, but current methods require complementary use.
- Further research is needed to improve the accuracy and consistency of digital shade matching.
