THE ROLE OF AI IN INTERPRETING PANORAMIC DENTAL X-RAYS A NARRATIVE REVIEW

Abstract

Background: Artificial intelligence (AI) is rapidly transforming the field of dental radiology, particularly in the interpretation of panoramic X-rays. Panoramic radiographs provide comprehensive visualization of teeth, jaws, and surrounding structures, making them critical for diagnosing a wide spectrum of dental and maxillofacial conditions. However, manual interpretation is time-intensive and susceptible to human error. The integration of AI, through machine learning (ML) and deep learning (DL) models, offers significant potential to enhance diagnostic accuracy, efficiency, and consistency, thereby improving patient outcomes and supporting clinical decision-making.

Objective: This narrative review aims to synthesize current knowledge on the application of AI in panoramic dental radiograph interpretation, highlighting its advantages, limitations, and future opportunities in dental diagnostics.

Main Discussion Points: The review explores AI-powered algorithms, particularly convolutional neural networks (CNNs), that have demonstrated strong performance in detecting caries, periodontal disease, implants, and other anomalies. Key advantages include improved diagnostic accuracy, reduced human error, real-time support for less experienced practitioners, and enhanced treatment planning. Limitations such as dataset quality, lack of standardization, interpretability challenges, and integration with existing clinical systems are critically discussed. Future directions emphasize AI-driven decision support systems, real-time diagnostics, and personalized treatment planning.

Conclusion: AI demonstrates strong potential to revolutionize panoramic X-ray interpretation by improving accuracy, efficiency, and accessibility in dental practice. While current findings are encouraging, further large-scale studies, standardized evaluation protocols, and robust clinical validation are needed to ensure safe and equitable implementation.