GPT-4V(ision) Unsuitable for Clinical Care and Education: A Clinician-Evaluated Assessment

Senthujan Senkaiahliyan, Augustin Toma, Jun Ma, An-Wen Chan, Andrew Ha +4 more
11/14/2023
cs.CV

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Abstract

OpenAI's large multimodal model, GPT-4V(ision), was recently developed for general image interpretation. However, less is known about its capabilities with medical image interpretation and diagnosis. Board-certified physicians and senior residents assessed GPT-4V's proficiency across a range of medical conditions using imaging modalities such as CT scans, MRIs, ECGs, and clinical photographs. Although GPT-4V is able to identify and explain medical images, its diagnostic accuracy and clinical decision-making abilities are poor, posing risks to patient safety. Despite the potential that large language models may have in enhancing medical education and delivery, the current limitations of GPT-4V in interpreting medical images reinforces the importance of appropriate caution when using it for clinical decision-making.

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Cite this paper

@article{senkaiahliyan2023gptvision,
  title  = {GPT-4V(ision) Unsuitable for Clinical Care and Education: A Clinician-Evaluated Assessment},
  author = {Senthujan Senkaiahliyan and Augustin Toma and Jun Ma and An-Wen Chan and Andrew Ha and Kevin R. An and Hrishikesh Suresh and Barry Rubin and Bo Wang},
  year   = {2023},
  eprint = {2403.12046},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.12046v1}
}

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