General-Purpose Large Language Models Versus a Domain-Specific Natural Language Processing Tool for Label Extraction From Chest Radiograph Reports

Plain language summary (for Research Letters only): GPT-4 outperformed a radiology domain–specific NLP model in classifying imaging findings from chest radiograph reports, both with and without predefined labels. Prompt engineering for context further improved performance. The findings indicate a role for LLMs to accelerate AI model development in radiology by automating data annotation.