ARTIFICIAL INTELLIGENCE IN DENTAL DIAGNOSTICS: ENHANCING ACCURACY AND PREDICTIVE OUTCOMES

Abstract

Artificial Intelligence (AI) is increasingly transforming the field of dentistry, particularly in the area of diagnostic accuracy and predictive outcomes. AI algorithms, including machine learning and deep learning models, can analyze radiographic images, cone-beam computed tomography (CBCT) scans, and intraoral photographs to detect early signs of dental caries, periodontal disease, and other oral pathologies. The integration of AI in dental diagnostics not only improves detection rates but also enables predictive modeling for disease progression, treatment planning, and patient-specific risk assessment.Moreover, AI-powered diagnostic systems reduce human error, enhance workflow efficiency, and support decision-making in both general dental practices and specialized clinics. Despite the promising advantages, challenges such as data privacy, algorithmic bias, and the need for standardized training protocols remain. This article explores current applications, benefits, limitations, and future directions of AI in dental diagnostics, emphasizing its potential to revolutionize patient-centered care and clinical outcomes.