[Expert consensus on the application of artificial intelligence in stomatology].
Authors
Affiliations (7)
Affiliations (7)
- Department of Geriatric Dentistry, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China.
- Department of Implantology, Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University & Guangdong Provincial Key Laboratory of Stomatology, Guangzhou 510055, China.
- Department of Cariology and Endodontic Diseases, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China.
- Department of Oral Implantology, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China.
- Department of Pediatric Dentistry, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China.
- Department of Oral and Maxillofacial Surgery, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China.
- Department of Orthodontics, Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University & Guangdong Provincial Key Laboratory of Stomatology, Guangzhou 510055, China.
Abstract
In recent years, artificial intelligence (AI) has rapidly advanced in the field of oral medicine, with applications extending across disease screening, diagnosis assistance, treatment planning, prognosis prediction, and dental education. Powered by deep learning and multimodal analytics, AI can efficiently integrate data from cone beam CT, intraoral scans, and electronic health records, enhancing precision and efficiency in managing dental caries, endodontic and periodontal diseases, oral mucosal lesions, and maxillofacial trauma. AI also contributes to omics research, biomaterial development, and laboratory automation, accelerating translational progress from basic science to clinical practice. Despite these advances, challenges as lack of standardized data governance, limited model interpretability, privacy and security risks, and insufficient clinical validation and regulatory frameworks still remain. This expert consensus provides a comprehensive overview of AI applications in dentistry, outlines core technical pathways, and proposes recommendations related to data governance, platform development, ethics, and regulatory requirements. It aims to provide practical and unified guidance for dental practitioners, healthcare institutions, researchers, and industry stakeholders, promoting safe, standardized, and sustainable development of AI in oral healthcare.