General-Purpose Large Language Models Versus a Domain-Specific Natural Language Processing Tool for Label Extraction From Chest Radiograph Reports
Cody Savage, Hyoungsun Park, Kijung Kwak, Andrew D. Smith, Steven Rothenberg, Vishwa S. Parekh, Florence X. Doo, Paul H. Yi
Abstract
GPT-4 outperformed a radiology domain-specific natural language processing 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 large language models to accelerate artificial intelligence model development in radiology by automating data annotation.
Topics & Concepts
MedicineChest radiographNatural language processingContext (archaeology)Domain (mathematical analysis)RadiologyArtificial intelligenceAnnotationRadiographyComputer scienceBiologyPaleontologyMathematical analysisMathematicsTopic ModelingArtificial Intelligence in Healthcare and EducationCOVID-19 diagnosis using AI