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TRV-2026-0985Version 1 · Certified

Written 2026-09-05 06:06:26 UTC · current record

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TRUVACE RECORD VERSION
record: TRV-2026-0985
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-09-05T06:06:26.293785Z
status: published
lens: g_space
sector: health
headline: Accuracy of General-Use Multimodal AI Platforms for Pell and Gregory Classification of Impacted Mandibular Third Molars
dek: Purpose The purpose of this study was to evaluate the performance of two general-use artificial intelligence models, ChatGPT and Grok, in classifying impacted mandibular third molars using the Pell and Gregory system on panoramic radiographs, compared with a resident consensus reference standard. Materials and methods One hundred panoramic radiographic images of impacted mandibular third molars were independently classified by two blinded resident reviewers using the Pell and Gregory classification system. Resid…
gain_title: Cases without consensus were excluded from the AI accuracy analysis. AI accuracy was calculated as the proportion of correct classifications among consensus cases, and the two models were compared using McNemar's test with continuity correction.
problem_title: (none)
trace_subject: (none)
gain_reading: Cases without consensus were excluded from the AI accuracy analysis. AI accuracy was calculated as the proportion of correct classifications among consensus cases, and the two models were compared using McNemar's test with continuity correction.
gain_evidence: (none)
problem_reading: (none)
problem_evidence: (none)
quick_read: Purpose The purpose of this study was to evaluate the performance of two general-use artificial intelligence models, ChatGPT and Grok, in classifying impacted mandibular third molars using the Pell and Gregory system on panoramic radiographs, compared with a resident consensus reference standard. Materials and methods One hundred panoramic radiographic images of impacted mandibular third molars were independently classified by two blinded resident reviewers using the Pell and Gregory classification system.

Resident consensus was defined as exact agreement between both reviewers; the 94 concordant classifications were confirmed by a board-certified oral and maxillofacial radiologist (the second author), blinded to the AI outputs, and served as the reference standard. Cases without consensus were excluded from the AI accuracy analysis.
limitation: 
tag: Evidence-backed gain
key_points: Purpose The purpose of this study was to evaluate the performance of two general-use artificial intelligence models, ChatGPT and Grok, in classifying impacted mandibular third molars using the Pell and Gregory system on panoramic radiographs, compared with a resident consensus reference standard. | Materials and methods One hundred panoramic radiographic images of impacted mandibular third molars were independently classified by two blinded resident reviewers using the Pell and Gregory classification system. | Resident consensus was defined as exact agreement between both reviewers; the 94 concordant classifications were confirmed by a board-certified oral and maxillofacial radiologist (the second author), blinded to the AI outputs, and served as the reference standard.
rundown: Purpose The purpose of this study was to evaluate the performance of two general-use artificial intelligence models, ChatGPT and Grok, in classifying impacted mandibular third molars using the Pell and Gregory system on panoramic radiographs, compared with a resident consensus reference standard. Materials and methods One hundred panoramic radiographic images of impacted mandibular third molars were independently classified by two blinded resident reviewers using the Pell and Gregory classification system.

Resident consensus was defined as exact agreement between both reviewers; the 94 concordant classifications were confirmed by a board-certified oral and maxillofacial radiologist (the second author), blinded to the AI outputs, and served as the reference standard. Cases without consensus were excluded from the AI accuracy analysis.
sources:
- peer_reviewed | Cureus | https://doi.org/10.7759/cureus.115713 | 2026-09-03
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