International dental journal · 2026
Artificial Intelligence Meets Oral Medicine: Extending the Capabilities of Human Intelligence.
СтатьяОбзорНазвание и аннотация: Перевод в очереди
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Ye Xinjian, Zha Tingfeng, Xie Xun, Xu Yi, Mei Li, Zhang Rui, Wang Zhiyong, Chen Qianming
Аннотация
OBJECTIVES: Oral medicine is an interdisciplinary field that focuses on non-odontogenic diseases. The emergence of artificial intelligence (AI) offers new opportunities to strengthen human perceptual, cognitive, and operational capacities. This review aims to provide clinicians and researchers with an explanatory, practical, and accessible overview of AI in oral medicine.
METHODS: This review synthesizes recent findings identified through structured online searches. Subtopics related to AI technologies in oral medicine were categorized into four areas: image recognition, decision-making support, therapy collaboration, and existing challenges. Particular emphasis was placed on oral mucosal diseases, oral cancer, and orofacial pain.
RESULTS: AI enhances clinical workflows by achieving high-accuracy lesion detection, segmentation, and classification from diverse image types. It enables data-driven diagnosis, risk stratification, and prognosis prediction. Furthermore, AI facilitates precise surgical planning, real-time guidance, and personalized postoperative management.
CONCLUSIONS: AI is poised to transform Oral Medicine into an intelligence-augmented discipline. However, its full clinical integration requires overcoming challenges related to data quality, algorithmic robustness, ethical governance, and the need for robust clinical validation.
METHODS: This review synthesizes recent findings identified through structured online searches. Subtopics related to AI technologies in oral medicine were categorized into four areas: image recognition, decision-making support, therapy collaboration, and existing challenges. Particular emphasis was placed on oral mucosal diseases, oral cancer, and orofacial pain.
RESULTS: AI enhances clinical workflows by achieving high-accuracy lesion detection, segmentation, and classification from diverse image types. It enables data-driven diagnosis, risk stratification, and prognosis prediction. Furthermore, AI facilitates precise surgical planning, real-time guidance, and personalized postoperative management.
CONCLUSIONS: AI is poised to transform Oral Medicine into an intelligence-augmented discipline. However, its full clinical integration requires overcoming challenges related to data quality, algorithmic robustness, ethical governance, and the need for robust clinical validation.