Evaluating the Accuracy and Diagnostic Reasoning of Multimodal Large Language Models in Interpreting Neuroradiology Cases From <i>RadioGraphics</i>.

ABSTRACT:

Objective

To evaluate the accuracy and reasoning capabilities of large multimodal language models compared with those of neuroradiology subspecialty-trained radiologists in neuroradiology case interpretation.

Materials and methods

This experimental study used custom-made 401 radiologic quizzes derived from articles published in RadioGraphics covering neuroradiology and head and neck topics (October 2020 to February 2024). We prompted the GPT-4 Turbo with Vision (GPT-4V), GPT-4 Omni, Gemini Flash, and Claude models to provide the top three differential diagnoses with a rationale and describe examination characteristics such as imaging modality, sequence, use of contrast, image plane, and body part. The temperature was adjusted to 0 and 1 (T1). Two neuroradiologists ans

SUBMITTER: Suh PS 

PROVIDER: S-EPMC12936569 | biostudies-literature | 2026 Mar

REPOSITORIES: biostudies-literature