Abstract

Artificial intelligence (AI) has moved rapidly from an experimental concept to a practical tool across the dental specialties. Machine learning and deep learning models are now being applied to radiographic interpretation, caries and periodontal disease detection, orthodontic diagnosis, endodontic anatomy assessment, and prosthodontic planning, often matching or approaching clinician-level performance on narrow, well-defined tasks. This mini review summarizes recent developments in AI applications across dentistry, highlights recurring methodological limitations reported in the literature, and outlines the ethical and regulatory considerations that will shape clinical adoption. While the evidence base is expanding quickly, most studies remain retrospective, single-center, and validated on limited datasets, underscoring the need for prospective, multi-center research before widespread clinical integration.

Keywords:Artificial intelligence; Dentistry; Deep learning; Diagnostic imaging; Machine learning