Primary study · included by 1 review

Accuracy of ChatGPT-Generated Information on Head and Neck and Oromaxillofacial Surgery: A Multicenter Collaborative Analysis.

Vaira 2023 · Vaira Luigi Angelo, Lechien Jerome R, Abbate Vincenzo, et al. · Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery · 2024

Included by

Accuracy of Large Language Models in Answering Dental Examination Questions: A Systematic Review and Meta-Analysis.
Non-Cochrane · other · 2026 · cited as Vaira 2023 · Table 1; reference list (refs 18-56)
Outcome this study informsPooled effectEvidenceCertainty
Accuracy (proportion of correct answers)
Any large language model vs Reference standard (official answer key, validated question bank or expert consensus) · Questions answered by LLMs (studies searched to January 2025)
Proportion, percent (random effects, Freeman-Tukey double arcsine) 63.69 [60.26, 67.06]39 studies · 17021 participantsGRADE not reported
Accuracy (proportion of correct answers)
Any large language model vs Reference standard (official answer key, validated question bank or expert consensus) · Questions answered by LLMs (studies searched to January 2025)
Leave-one-out analysis demonstrated stable pooled accuracy estimates ranging from 64.13% to 65.66%, with the most influential study (Chau et al) altering results by 1.96% upon exclusionNRGRADE not reported
Accuracy (proportion of correct answers)
Any large language model vs Reference standard (official answer key, validated question bank or expert consensus) · Questions answered by LLMs (studies searched to January 2025)
Proportion, percent (leave-one-out) 63.47 [62.69, 64.25]NRGRADE not reported
Accuracy (proportion of correct answers)
Any large language model vs Reference standard (official answer key, validated question bank or expert consensus) · Questions answered by LLMs (studies searched to January 2025)
Prediction interval [29.65; 91.71]39 studies · 17021 participantsGRADE not reported
Accuracy (proportion of correct answers)
Any large language model vs Reference standard (official answer key, validated question bank or expert consensus) · Questions answered by LLMs (studies searched to January 2025)
Proportion, percent (leave-one-out) 65.04 [64.26, 65.81]NRGRADE not reported
Accuracy (proportion of correct answers)
Any large language model vs Reference standard (official answer key, validated question bank or expert consensus) · Questions answered by LLMs (studies searched to January 2025)
Proportion, percent (fixed effect) 64.87 [64.13, 65.61]39 studies · 17021 participantsGRADE not reported
Accuracy (proportion of correct answers)
Any large language model vs Reference standard (official answer key, validated question bank or expert consensus) · Questions answered by LLMs (studies searched to January 2025)
Proportion, percent (leave-one-out) 66.83 [66.07, 67.60]NRGRADE not reported
Accuracy (proportion of correct answers)
Any large language model vs Reference standard (official answer key, validated question bank or expert consensus) · Questions answered by LLMs (studies searched to January 2025)
Proportion, percent (random effects, Freeman-Tukey double arcsine) 65.43 [61.88, 68.89]NRGRADE not reported

1 including review in total.