Evaluating GPT-4 with Vision on Detection of Radiological Findings on Chest Radiographs
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Abstract (arXiv)
The study examines the application of GPT-4V, a multi-modal large language model equipped with visual recognition, in detecting radiological findings from a set of 100 chest radiographs and suggests that GPT-4V is currently not ready for real-world diagnostic usage in interpreting chest radiographs.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 6 references that are in the map. First posted on arXiv 22 Mar 2024.
Builds on
3 of 6 references.
References · 3
- 2017ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseasescited by 972
- 2023The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)cited by 681
- 2023GPT-4V(ision) as a Generalist Evaluator for Vision-Language Taskscited by 119
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- 2024GPT-4V Cannot Generate Radiology Reports Yet
- 2023Holistic Evaluation of GPT-4V for Biomedical Imaging
- 2023GPT-4V(ision) Unsuitable for Clinical Care and Education: A Clinician-Evaluated Assessment
- 2025Vision-Language Models for Automated Chest X-ray Interpretation: Leveraging ViT and GPT-2
- 2024Hidden flaws behind expert-level accuracy of multimodal GPT-4 vision in medicine
- 2023Multimodal ChatGPT for Medical Applications: an Experimental Study of GPT-4V
- 2025Evaluating ChatGPT's Performance in Classifying Pneumonia from Chest X-Ray Images
- 2023Can GPT-4V(ision) Serve Medical Applications? Case Studies on GPT-4V for Multimodal Medical Diagnosis