INTEGRATION OF ARTIFICIAL INTELLIGENCE IN DIAGNOSTIC DENTISTRY: CURRENT TRENDS AND FUTURE POSSIBILITIES – A NARRATIVE REVIEW

Abstract

Background: Artificial intelligence (AI) has emerged as a transformative force in modern healthcare, with growing applications in dentistry. As oral diseases such as dental caries and periodontal conditions continue to affect billions worldwide, the integration of AI offers a novel approach to improving diagnostic accuracy, reducing clinician variability, and streamlining decision-making processes. The increasing digitalization of dental practices underscores the need to explore how AI can be leveraged for timely and precise diagnostics.

Objective: This narrative review aims to explore the current applications and future possibilities of AI in diagnostic dentistry, with a specific focus on caries detection, radiographic analysis, and the development of personalized dental care planning.

Main Discussion Points: The review synthesizes literature highlighting AI’s capability in enhancing caries detection using convolutional neural networks, improving radiographic interpretation through automated lesion recognition, and aiding in patient-specific risk prediction. It also discusses limitations in existing research, including small sample sizes, lack of randomized controlled trials, inconsistent outcome measures, and limited generalizability across diverse clinical settings. Methodological and publication biases are identified as key concerns, and the need for standardized clinical guidelines is emphasized.

Conclusion: AI holds considerable promise in elevating diagnostic dentistry, offering tools that can complement clinical expertise and enhance patient care. However, current evidence, while promising, remains preliminary. Robust clinical trials and interdisciplinary collaboration are essential to validate AI’s real-world effectiveness and ensure ethical, equitable integration into dental practice.