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Large language models for structured reporting in radiology: performance of GPT-4, ChatGPT-3.5, Perplexity and Bing
Carlo A Mallio1, Andrea C Sertorio2, Caterina Bernetti2
1Research Unit of Radiology, Department of Medicine and Surgery, Fondazione Policlinico Universitario Campus Bio-Medico, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo, 200, 00128, Rome, RM, Italy. c.mallio@policlinicocampus.it.
Abstract:
Structured reporting may improve the radiological workflow and communication among physicians. Artificial intelligence applications in medicine are growing fast. Large language models (LLMs) are recently gaining importance as valuable tools in radiology and are currently being tested for the critical task of structured reporting. We compared four LLMs models in terms of knowledge on structured reporting and templates proposal. LLMs hold a great potential for generating structured reports in radiology but additional formal validations are needed on this topic.
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