ArticleImaging science in dentistry2026
Reliability of the QUADAS-2 checklist in AI-based medical imaging: A comparison of human reviewers and ChatGPT-4o.
Article in Imaging science in dentistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Purpose: Artificial intelligence is reshaping medical imaging, yet reliable bias assessment in this context remains insufficiently studied. It remains unclear whether the widely used QUADAS-2 checklist provides reproducible evaluations in AI-based imaging studies. Therefore, we compared human and ChatGPT-4o assessments to examine the reproducibility of QUADAS-2 in this setting. Materials and Methods: Twenty PubMed-indexed AI-based dental imaging studies were analyzed by five human reviewers and five independent ChatGPT-4o runs using identical categorical outputs. Reliability within and between groups was quantified using Fleiss' kappa. Results: Human agreement ranged from -0.07 to 0.22, with only the reference standard domain reaching fair reliability (κ=0.22, Conclusion: These findings suggest that QUADAS-2 may have limited reproducibility when applied to AI-based imaging research under the present study conditions, although the observed inconsistency may also reflect features of the study design and assessment setting. These findings support consideration of AI-specific tools such as QUADAS-AI for future bias assessment in AI-driven medical imaging.
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