Role of Artificial Intelligence in Oral Medicine and Radiology: A Review

Abstract Artificial Intelligence (AI) has emerged as a transformative tool in oral medicine and radiology, enhancing diagnostic accuracy and clinical decision-making. This review explores the role of AI, particularly machine learning (ML) and deep learning (DL), in improving the detection and management of various oral conditions, including jaw lesions, oral squamous cell carcinoma (OSCC), salivary gland disorders, temporomandibular joint (TMJ) disorders, oral potentially malignant disorders (OPMDs), and mandibular fractures. AI-driven models, such as convolutional neural networks (CNNs) and radiomics, have demonstrated high accuracy in identifying maxillofacial cysts, tumors, and TMJ osteoarthritis using imaging modalities like cone-beam computed tomography (CBCT), CT, and MRI. These models often outperform or match experienced radiologists, offering faster, objective, and non-invasive diagnostic support. Additionally, AI facilitates early detection of OPMDs and OSCC by analyzing clinical and imaging data, enabling personalized treatment planning and reducing diagnostic variability. By integrating AI-based clinical decision support systems (CDSS), dental practitioners can achieve improved patient outcomes through enhanced diagnostic precision and efficiency. This review underscores AI’s potential to revolutionize oral healthcare while highlighting the importance of expert-annotated datasets and standardized validation processes for developing reliable AI models.