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April 10, 2026British Journal of Ophthalmology0 citations

Publicly available multimodal large language models for ocular surface infections: benchmarking against corneal specialists in triage, diagnosis and treatment

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CCCarlos Campo-BeamudARAlfonso RuizJQJesús Bastante Quijano

Key Points

  • To assess the effectiveness of multimodal large language models in diagnosing ocular surface infections compared to corneal specialists.
  • Benchmarking multimodal LLMs against expert evaluations.
  • Incorporating clinical context and slit-lamp images for analysis.
  • Evaluating therapeutic reasoning and pathogen identification.
  • Multimodal LLMs achieved near-expert-level diagnosis and triage performance.
  • Identified gaps in therapeutic reasoning and rare pathogen recognition.
  • Potential for these models to support care in resource-limited settings.

Abstract

Publicly accessible multimodal LLMs can approach expert-level performance in diagnosis and triage when provided with clinical context and slit-lamp images. Gaps in therapeutic reasoning and rare pathogen recognition underscore the need for targeted refinement and validation. These models may complement specialist care, supporting rapid triage and integration with molecular or metagenomic diagnostics, especially in resource-limited settings.

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Cite This Study

Campo-Beamud et al. (2026) studied this question.

synapsesocial.com/papers/69d893eb6c1944d70ce04ec1https://doi.org/10.1136/bjo-2025-328867
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