Evaluation of large language models for clinical sign-based oral assessment in dogs compared with veterinary practitioners


KOCAMAN Y., Yanmaz L. E., OKUR S., TURGUT F., Suzak Kocaman I., ASLAN CANATAN V., ...More

Veterinary Journal, vol.317, 2026 (SCI-Expanded, Scopus)

  • Publication Type: Article / Article
  • Volume: 317
  • Publication Date: 2026
  • Doi Number: 10.1016/j.tvjl.2026.106611
  • Journal Name: Veterinary Journal
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, EMBASE, MEDLINE
  • Keywords: ChatGPT, Claude-Sonnet, Dentistry, Gemini, Gingivitis, Image-analysis
  • Ataturk University Affiliated: Yes

Abstract

This study aimed to evaluate the diagnostic performance of Large Language Models (LLMs) in canine oral assessment by comparing their accuracy and agreement with a panel of expert veterinary academicians. Sixty lateral oral photographs from clinical canine cases were evaluated for nine oral clinical signs by novice veterinarians, a panel of expert veterinary academicians, and four LLMs (ChatGPT-5.1, ChatGPT-5.1 Thinking, Claude-Sonnet 4.5, Gemini-Pro 3). Expert consensus served as the reference standard. Intra-model consistency testing demonstrated substantial reliability for Claude-Sonnet 4.5 (90 % full agreement; κ = 0.75), moderate reliability for Gemini-Pro 3 (70 %; κ = 0.57) and ChatGPT-5.1 (50 %; κ = 0.43), and weak reliability for ChatGPT-5.1 Thinking (30 %; κ = 0.33). Overall diagnostic accuracy across evaluators ranged from 33.3 % to 95 %. Novice veterinarians achieved statistically significant agreement in six clinical signs (e.g., calculus κ = 0.577; p < 0.001; pigmentation κ = 0.378; p < 0.001), outperforming all LLMs in diagnostic breadth. Among LLMs, ChatGPT-5.1 and ChatGPT-5.1 Thinking reached significant weak-to-moderate agreement for several clinical signs (e.g., calculus κ = 0.356–0.485; p ≤ 0.001). LLMs outperformed novices only in traumatic lesions (Gemini-Pro 3 κ = 0.290; p = 0.001). All evaluators exhibited chance-level performance for tooth fractures. In conclusion, novice veterinarians demonstrated higher diagnostic consistency and agreement with experts than all evaluated LLMs. Although ChatGPT-5.1 models showed the strongest AI performance, current LLMs remain insufficient for independent diagnostic use in veterinary dentistry.