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Artificial Intelligence Applications in the Diagnosis and Management of Periodontitis: A Review

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Systematic review finds AI improves diagnostic accuracy and treatment planning in periodontitis, indicating potential for clinical use.

The review aims to explore how artificial intelligence can enhance the diagnosis and management of periodontitis by evaluating existing applications and identifying research gaps.
Conducted a systematic review searching six major databases for studies applying AI to periodontal disease from 2010 to 2025.
Included original peer-reviewed studies reporting at least one quantitative performance metric about AI applications in periodontitis.
Assessed risk of bias using a domain-based tool and synthesized results narratively due to heterogeneity.
AI demonstrated diagnostic accuracies of 73.0 to 99.4% (median ≈91%) for radiographic detection of alveolar bone loss.
Classification studies showed accuracies from 70 to 98% (median ≈87%), with higher performance in advanced stages of disease.
Prognosis prediction models reported accuracies between 73 and 95% (median ≈80%), with some models achieving C-statistics up to 0.88.

Noor et al. (2026) studied this question.

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