Artificial intelligence in panoramic images—clinical aid to a dentist

Abstract

Aim: Artificial intelligence (AI) has significantly influenced healthcare, enhancing diagnostic and therapeutic capabilities. This study evaluates the effectiveness of an AI-generated output within actual clinical environments, analyzing its precision compared to conventional interpretation techniques. Methods: A cross-sectional observational study assessed the reliability of the VELMENI AI platform in detecting dental issues on panoramic radiographs. Three hundred radiographs from the Sibar Institute of Dental Sciences were used, with four experienced readers trained on the AI platform. Each reader independently identified caries, restorations, and prostheses using the AI system. Diagnoses by dentists and the AI tool were compared, ensuring rigorous analysis and ethical standards. Results: This study examined the agreement between four human observers and an AI system in assessing caries, fixed prostheses, and restorations using Cohen’s weighted kappa. High reliability was found among the human observers, with the AI system demonstrating even greater consistency. The results were statistically significant, demonstrating strong agreement. Fleiss’ multi-rater kappa confirmed high overall agreement among all five raters. However, moderate agreement in caries assessment highlighted the need for enhanced training and guidelines. Conclusions: This study underscores AI’s potential in dental diagnostics, excelling in fixed prosthesis assessment while facing challenges in caries detection. Improved training and datasets are required for better clinician capabilities. The findings suggest AI-human collaboration is a promising future direction for dental diagnostics.

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