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

Senthujan Senkaiahliyan, Augustin Toma, Jun Ma, An-Wen Chan, Andrew Ha, Kevin R An, Hrishikesh Suresh, Barry Rubin, Bo Wang
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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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GPT-4V(视力)不适合临床护理和教育:一项临床评估
OpenAI的大型多模态模型GPT-4V(视觉)最近被开发用于一般图像解释。然而,人们对其在医学图像解释和诊断方面的能力知之甚少。委员会认证的医生和高级住院医师使用CT扫描、核磁共振、心电图和临床照片等成像方式评估GPT-4V在一系列医疗条件下的熟练程度。虽然GPT-4V能够识别和解释医学图像,但其诊断准确性和临床决策能力较差,给患者安全带来风险。尽管大型语言模型可能在加强医学教育和传播方面具有潜力,但目前GPT-4V在解释医学图像方面的局限性强化了在将其用于临床决策时适当谨慎的重要性。
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