Ying Yuan, Hao Zhou, Bo Wang, Chengrun Li, Baijuan Gong, Zhimin Li
It focuses on specific application scenarios of AI-based models and evaluates their performance, and additionally highlights the limitations and promising future directions, providing insights to advance the clinical applications of AI in dentistry.
The application of artificial intelligence (AI) technologies in the management of oral diseases is rapidly increasing, encompassing etiopathogenesis, disease course, diagnosis, treatment plans, and postoperative care. AI demonstrates exceptional performance in enhancing diagnostic accuracy and supporting clinical decision-making. This review provides a comprehensive overview of AI in dentistry, elucidating the neural network architectures and major implementation methods of AI. It focuses on specific application scenarios of AI-based models and evaluates their performance, and additionally highlights the limitations and promising future directions, providing insights to advance the clinical applications of AI in dentistry.