Accepted for/Published in: JMIR Research Protocols
Date Submitted: Nov 5, 2024
Date Accepted: Jun 20, 2025
Evaluating the efficacy of Artificial Intelligence assisted appliances in selection of tooth shade: An observational study
ABSTRACT
Background:
The instruments used for shade matching are always evolving because patients' demands for more aesthetics are driving up the bar for accuracy in tooth shade determination. A number of variables, including incident light, light reflection, light absorption, the visual matching by the observer, and the object's in the surroundings, can influence the complex phenomenon of color perception.
Objective:
This study protocol is to compare and evaluate the efficacy of AI assisted appliances in selecting the shade of tooth.
Methods:
The observational study will be conducted in the department of prosthodontics and crown & bridge. A total of 221 subjects will be recruited from the Out Patient Department [OPD] of Prosthodontics and Crown & Bridge. Informed consent will be taken from subjects. Subjects who fulfill the inclusion criteria will be screened for the study. The shade selection will be done of the study subjects using a smartphone and DSLR camera and intraoral scanner. Statistical analysis will include sensitivity analyses, sub-group analyses and specificity analyses. We expect to present, user-friendly, nontechnique-sensitive, existing, readily available, economic devices in the field of dentistry for shade selection.
Results:
The study's anticipated results indicate that DSLR and smartphone cameras will select shades just as effectively as intraoral scanners.
Conclusions:
This study will set a standard protocol for the use of AI assisted appliances i.e. Smartphone camera and DSLR camera for shade selection in the field of dentistry. We intend to showcase devices that are user-friendly and easy to operate, making them accessible for dental professionals with varying levels of experience. Clinical Trial: CTRI/2024/07/070002
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.