Exploring the Boundaries of GPT-4 in Radiology: Microsoft and Harvard find GPT-4 to excel or match current SOTA radiology-specific models in text-based applications for radiology reports, with ~10% absolute improvement in certain tasks

The recent success of general-domain large language models (LLMs) has significantly changed the natural language processing paradigm towards a unified foundation model across domains and applications. In this paper, we focus on assessing the performance of GPT-4, the most capable LLM so far, on the text-based applications for radiology reports, comparing against state-of-the-art (SOTA) radiology-specific models. Exploring various prompting strategies, we evaluated GPT-4 on a diverse range of com...

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