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GPT-4 Vision: Multi-Modal Evolution of ChatGPT and Potential Role in Radiology.

Ramin Javan1, Theodore Kim1, Navid Mostaghni2

  • 1Department of Radiology, George Washington University School of Medicine and Health Sciences, Washington, USA.

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Summary
This summary is machine-generated.

GPT-4 Vision (GPT-4V), a large multimodal model, shows potential for enhancing radiology workflows by analyzing images and aiding decision support. However, current limitations require further development before clinical integration.

Keywords:
chatgptgpt-4gpt-4 visionlarge language models (llms)large multimodal modellmmmultimodal ai

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Area of Science:

  • Artificial Intelligence
  • Multimodal AI
  • Radiology

Background:

  • Large language models (LLMs) are evolving into large multimodal models (LMMs) like GPT-4 Vision (GPT-4V).
  • Advancements in AI offer potential to improve radiology workflows and clinical decision support.

Purpose of the Study:

  • To explore potential applications of GPT-4V in radiology.
  • To evaluate GPT-4V's performance on various radiology-related tasks.

Main Methods:

  • GPT-4V capabilities were assessed using diverse image sources, including web images, teaching files, and sketches.
  • Tasks included scientific figure analysis, radiologic image reporting, image comparison, handwriting interpretation, sketch-to-code, and artistic expression.

Main Results:

  • GPT-4V demonstrated proficiency in image classification, entity counting, image comparison, and deciphering handwriting/sketches.
  • Limitations were observed in fracture detection, lesion size discernment, complex diagram interpretation, and consistent radiologic finding characterization.

Conclusions:

  • GPT-4V shows promise for radiology but requires further training to address reliability gaps before clinical use.
  • Future iterations could support radiology tasks, but human expertise remains crucial for safe and ethical practice.