Author:
Senkaiahliyan M. Senthujan,Toma Augustin,Ma Jun,Chan An-Wen,Ha Andrew,An Kevin R.,Suresh Hrishikesh,Rubin Barry,Wang Bo
Abstract
AbstractOpenAI’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.
Publisher
Cold Spring Harbor Laboratory
Reference7 articles.
1. “Large language models in medicine;Nature Medicine,2023
2. “Large language models encode clinical knowledge;Nature,2023
3. OpenAI, “Gpt-4v(ision) system card,” 2023.
4. Multimodal biomedical AI
5. A. J. Nashwan , A. A. AbuJaber , and A. AbuJaber , “Harnessing the power of large language models (llms) for electronic health records (ehrs) optimization,” Cureus, vol. 15, no. 7, 2023.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献