Aashna D*, Prathap MS, S Vidhyadhara Shetty, Nithin Suvarna, Rucha Harde and Khatheeja Thasneem

Department of Conservative Dentistry and Endodontics, Yenepoya Dental College, Mangalore, Karnataka, India

*Corresponding Author: Aashna D, Department of Conservative Dentistry and Endodontics, Yenepoya Dental College, Mangalore, Karnataka, India.

Received: September 16, 2025; Published: September 27, 2025

Abstract

AI has been a significant force in healthcare for quite some time, and its impact in dentistry is increasingly evident. It can address clinical challenges and enhance the efficiency of practitioners. Lighting conditions, color space models, shade matching devices, and the type of AI algorithm affect the accuracy of the prediction of dental shades for restorative procedures. Various neural networks and knowledge-based systems have shown increased accuracy in predicting dental shades. AI models, including neural networks, CNNs, fuzzy logic, GANs, RNNs, and random forests, are utilised in these processes. The review highlights the use of AI, fuzzy logic, and CNNs in shade matching in restorative procedures in dentistry. Rapid AI advancements support tooth shade selection, disease classification, bone loss evaluation, severity grading, image analysis, and early detection of problems. Over the last decade, AI-driven innovations have generated increased global research interest. Like other medical fields, dentistry is increasingly adopting AI, driven by the growing amount of patient data that requires more innovative software for organization and analysis. AI offers benefits throughout the entire patient journey, from initial department visits to treatment completion and follow-ups, aiding dental and medical professionals. While AI is unlikely to replace dentists in the near future, learning how to incorporate it into future workflow effectively is crucial for enhancing patient care.
Artificial intelligence (AI), a subset of computer science, is widely utilised in various industries; however, its application in dentistry remains relatively limited. Most research focuses on automating dental image analysis, predicting diseases, forecasting treatment outcomes, and enhancing technologies such as 3D printing, shade matching, and electronic apex locators. This overview explains key AI concepts, explores potential applications of fuzzy logic and convolutional neural networks (CNNs) in shade matching in restorative dentistry, and discusses the challenges and limitations of incorporating AI into dental practices.

Keywords: Artificial Intelligence; Fuzzy Logic; Convolutional Neural Networks; Dental Shade Selection

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Citation

Citation: Aashna D., et al. “Transforming Shade Selection in Dentistry: A Review on Artificial Intelligence-Fuzzy Logic and Convolutional Neural Networks".Acta Scientific Dental Sciences 9.10 (2025): 55-65.

Copyright

Copyright: © 2025 Aashna D., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.