Artificial Intelligence in Contemporary Dentistry: Applications Across Dental Specialties and Future Challenges.
Authors
Affiliations (7)
Affiliations (7)
- Department of Oral and Maxillofacial Surgery, Rajasthan Dental College and Hospital, Nirwan University, Jaipur, IND.
- Department of Conservative Dentistry and Endodontics, North Bengal Dental College and Hospital, Sushrutanagar, IND.
- Department of Conservative Dentistry and Endodontics, Bharati Vidyapeeth (Deemed to be University) Dental College and Hospital, Sangli, IND.
- Department of Periodontology, Guru Gobind Singh College of Dental Sciences and Research Centre, Burhanpur, IND.
- Department of Prosthodontics and Crown and Bridge, SGT Dental College and Hospital, Gurgaon, IND.
- Department of Community Medicine, Kalinga Institute of Medical Sciences, KIIT University, Bhubaneswar, IND.
- Department of Pedodontics and Preventive Dentistry, Maitri College of Dentistry and Research Centre, Durg, IND.
Abstract
Modern artificial intelligence (AI) is increasingly shaping contemporary dental practice through efficient diagnosis, improved treatment planning, and patient personalization across various settings. By leveraging innovations in computer vision, deep learning, and multimodal pattern recognition, computational models are being applied across the major fields of dentistry today. These AI-based approaches are used for automated lesion detection in diagnostic imaging, precision alignment in orthodontics, root canal mapping in endodontics, and robotic assistance in surgical procedures. Despite the substantial improvements in diagnostic accuracy, objectivity, and efficiency, there are several major challenges with implementing these technologies into clinical practice. These challenges include algorithm bias, data privacy concerns, the absence of regulatory guidelines for the development of such tools, and cost. This review aims to provide an overview of the applications of artificial intelligence in the different fields of dentistry, to highlight the current challenges and directions for future research and development, and to discuss the potential of generative language models, real-time augmented reality (AR), and the prediction of dental healthcare outcomes.