Artificial Intelligence and its Implications in the Management of Orofacial Diseases - A Systematic Review

This study aimed to evaluate artificial intelligence’s integration into dental practice and its impact on clinical outcomes.

Research papers titled “Artificial Intelligence and its Implications in Dentistry” were searched on PubMed, ResearchGate, Sci-Hub, and Crossref from 2018 onwards. The selected publications were independently evaluated, reviewed for eligibility, and meticulously analyzed to meet all inclusion criteria.

This mini-review of 46 studies (2018-2024) explored AI applications in dentistry, particularly machine learning and deep learning. AI was applied for diagnosis in 19 studies, treatment planning in 3 studies, and both diagnosis and treatment in 18 studies. It was used for detection in 15 studies, segmentation in 7 studies, and classification in 4 studies, with the largest sample size being 7,245 patients focused on oral cancer detection. The studies used diverse imaging modalities, underscoring AI's broad applicability in the field.

Artificial intelligence in dentistry holds significant promise, particularly in the realm of diagnosis. The significant patient sample sizes and diverse imaging techniques further validate AI's potential to enhance diagnostic accuracy and treatment efficiency. As AI continues to evolve, its integration into dental practice is likely to become increasingly essential, where it should complement rather than replace human clinical expertise with more research needed before it can be widely used in clinical settings.