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Kurz, C.* ; Merzhevich, T.* ; Eskofier, B.M. ; Kather, J.N.* ; Gmeiner, B.*

Benchmarking vision-language models for diagnostics in emergency and critical care settings.

NPJ Digit. Med. 8:423 (2025)

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The applicability of vision-language models (VLMs) for acute care in emergency and intensive care units remains underexplored. Using a multimodal dataset of diagnostic questions involving medical images and clinical context, we benchmarked several small open-source VLMs against GPT-4o. While open models demonstrated limited diagnostic accuracy (up to 40.4%), GPT-4o significantly outperformed them (68.1%). Findings highlight the need for specialized training and optimization to improve open-source VLMs for acute care applications.

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