Detection accuracy of an AI platform for dental treatment features on panoramic radiographs – tooth- and patient-level analyses
Abstract
Artificial intelligence (AI) has shown promise in dental imaging, yet its reliability for comprehensive diagnostic charting from panoramic radiographs (PAN) remains uncertain. We evaluated the diagnostic performance of a commercial AI platform (Diagnocat™, San Francisco, USA) in detecting common dental treatment features on PAN images. In this retrospective study, 147 patients (4,148 teeth) were analyzed against the consensus of two experienced readers. Tooth-level performance was assessed for missing teeth, fillings, crowns, pontics, endodontic treatments, orthodontic appliances, and implants, using patient-clustered nonparametric bootstrapping used to account for within-patient correlations. At the tooth level, the AI achieved high diagnostic accuracy across features (94.9–99.9%), with nearly perfect results for missing teeth, crowns, pontics, and implants. However, under a stringent patient-level “perfect match” criterion requiring error-free full-mouth reports, the AI succeeded in only 56.5% of cases (95% CI, 48.4–64.2%). Errors were most often related to fillings (57.3%) and endodontic treatments (19.5%). These findings highlight a critical gap between high per-tooth accuracy and clinically meaningful patient-level performance. These findings underscore that while the AI performs strongly at the tooth level, its patient-level performance is insufficient for autonomous diagnostic charting.
Read the paper
Related studies
- Global, regional, and national burden of hepatitis B, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
- A meta‐analysis of anal cancer incidence by risk group: Toward a unified anal cancer risk scale
- Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021
- Exercise interventions in Alzheimer's disease: A systematic review and meta-analysis of randomized controlled trials
- Prognostic Significance of Carbonic Anhydrase IX Expression in Cancer Patients: A Meta-Analysis
- Glucocorticoid Resistance: Is It a Requisite for Increased Cytokine Production in Depression? A Systematic Review and Meta-Analysis
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.