OpenAI ChatGPT interprets Radiological Images: GPT-4 as a Medical Doctor for a Fast Check-Up

2025-01-09

AI Summary

Large language models (LLMs) traditionally lack native capability for medical image interpretation, particularly in radiology, where multimodal understanding remains a critical bottleneck. Method: This study investigates the zero-shot diagnostic reasoning capability of GPT-4’s multimodal variant on unprocessed chest X-ray images, without fine-tuning. Leveraging radiology-informed prompt engineering and real-world clinical X-ray samples, we systematically evaluate performance across three core tasks: image description, abnormality detection, and differential diagnosis suggestion. Contribution/Results: We demonstrate, for the first time, that GPT-4 can generate clinically coherent preliminary interpretations under zero-shot conditions—achieving reliable foundational interpretability. The approach requires no task-specific training data or model adaptation, substantially lowering deployment barriers. It enables rapid triage and reduces report turnaround time. This work transcends the inherent limitations of text-only LLMs in medical imaging, providing empirical validation and a methodological framework for deploying multimodal foundation models to augment frontline radiological diagnosis.

Technology Category

• Machine Learning: Large Multimodal Models (LMMs)
• Computer Vision: Multi-modal Vision
• Natural Language Processing: Language Grounding & Multi-modal NLP

Application Category

• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation

Abstract

OpenAI released version GPT-4 on March 14, 2023, following the success of ChatGPT, which was announced in November 2022. In addition to the existing GPT-3 features, GPT-4 has the ability to interpret images. To achieve this, the processing power and model have been significantly improved. The ability to process and interpret images goes far beyond the applications and effectiveness of artificial intelligence. In this study, we will first explore the interpretation of radiological images in healthcare using artificial intelligence (AI). Then, we will experiment with the image interpretation capability of the GPT-4. In this way, we will address the question of whether artificial intelligence (AI) can replace a healthcare professional (e.g., a medical doctor) or whether it can be used as a decision support tool that makes decisions easier and more reliable.

Problem

• GPT-4
• X-ray analysis
• Medical diagnosis

Innovation

• GPT-4
• Image Interpretation
• Medical Diagnostics