Revolution or risk?-Assessing the potential and challenges of GPT-4V in radiologic image interpretation.

ABSTRACT:

Objectives

ChatGPT-4 Vision (GPT-4V) is a state-of-the-art multimodal large language model (LLM) that may be queried using images. We aimed to evaluate the tool's diagnostic performance when autonomously assessing clinical imaging studies.

Materials and methods

A total of 206 imaging studies (i.e., radiography (n = 60), CT (n = 60), MRI (n = 60), and angiography (n = 26)) with unequivocal findings and established reference diagnoses from the radiologic practice of a large university hospital were accessed. Readings were performed uncontextualized, with only the image provided, and contextualized, with additional clinical and demographic information. Responses were assessed along multiple diagnostic dimensions and analyzed using appropriate statistical tests.

Results

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SUBMITTER: Huppertz MS 

PROVIDER: S-EPMC11836096 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature