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

• Published in: arXiv.org
• Main Authors: Senkaiahliyan, Senthujan, Toma, Augustin, Ma, Jun, An-Wen, Chan, Ha, Andrew, An, Kevin R, Suresh, Hrishikesh, Rubin, Barry, Wang, Bo
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 14.11.2023
• Subjects: Computed tomography; Computer Science - Computer Vision and Pattern Recognition; Decision making; Education; Large language models; Medical imaging
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.2403.12046

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.