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TRV-2026-1166Certified recordPeer-reviewed

Image-Based Diagnosis of Oral Lesions: Performance of a Vision-Language Model versus Human Clinicians

Objective To evaluate the real-world diagnostic performance of a multimodal large language model (LLM) for image-based assessment of oral mucosal lesions compared with clinicians of varying expertise. Study design Prospective international multicenter diagnostic accuracy study. Setting Twenty university and tertiary head and neck centers in Italy, Belgium, France, Spain, and Israel. Methods We enrolled 350 consecutive patients (320 with oral lesions, 30 with normal mucosa). Clinical photographs and basic epidemi…

Health · P Space — documented harm · certified 2026-09-22 · v1 · article view · machine-readable

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Image-Based Diagnosis of Oral Lesions: Performance of a Vision-Language Model versus Human Clinicians: Urgency assignment was correct in 70% of cases (κ = 0.716), with a conservative tendency to overestimate risk.

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Truvace Impact Record TRV-2026-1166, v1: “Image-Based Diagnosis of Oral Lesions: Performance of a Vision-Language Model versus Human Clinicians.” Truvace, 2026-09-22. /record/TRV-2026-1166 (accessed at citation time). sha256 d25b8eb0703f13d7…

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