Capability of GPT-4V(ision) in the Japanese National Medical Licensing Examination: Evaluation Study.

ABSTRACT:

Background

Previous research applying large language models (LLMs) to medicine was focused on text-based information. Recently, multimodal variants of LLMs acquired the capability of recognizing images.

Objective

We aim to evaluate the image recognition capability of generative pretrained transformer (GPT)-4V, a recent multimodal LLM developed by OpenAI, in the medical field by testing how visual information affects its performance to answer questions in the 117th Japanese National Medical Licensing Examination.

Methods

We focused on 108 questions that had 1 or more images as part of a question and presented GPT-4V with the same questions under two conditions: (1) with both the question text and associated images and (2) with the question text only. We then compared t

SUBMITTER: Nakao T 

PROVIDER: S-EPMC10966435 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature