Abstract
Background: The use of artificial intelligence (AI) is rapidly growing in the field of dental medicine and in oral and maxillofacial surgery (OMS). The aim of the present review is to assess current applications of AI in OMS, to evaluate their advantages and limitations, and to identify areas requiring further research. Materials and Methods: A comprehensive search was conducted using PubMed, Scopus, and Google Scholar, with targeted keywords including “artificial intelligence,” “deep learning,” “machine learning,” “oral surgery,” “maxillofacial surgery,” and “diagnosis “Artificial Intelligence” OR “Machine Learning” OR “Deep Learning” AND “Oral and Maxillofacial Surgery” OR “Oral Surgery” OR “Maxillofacial Surgery” AND “Diagnosis”. Of 308 identified studies, 37 met the inclusion criteria focusing on AI-assisted detection interpretation and surgical planning in OMS. Results: AI is effective in identifying anatomical landmarks, evaluating lesions and cysts, diagnosing bone disease like medication-related osteonecrosis of jaws (MRONJ), planning dental implants, and aiding in the classification of fractures and temporomandibular joint (TMJ) disorders. AI can match or outperform human experts in various diagnostic tasks, particularly in panoramic and cone-beam computed tomography (CBCT) image analysis. AI shows promise in early detection of impacted and supernumerary teeth, maxillofacial pathologies, neoplastic conditions, and soft tissue calcifications. Limitations: However, substantial methodological heterogeneity, inconsistent reporting of AI performance metrics, and limited external validation across the included studies constrain direct comparison of results and assessment of the generalizability of reported AI performance. Conclusions: AI may assist clinicians in diagnostic and treatment-related decision-making, but current evidence does not support its use as a replacement for comprehensive clinical assessment and professional judgment.