Clinical reasoning from real-world oncology reports using large language models

Abstract

This study shows that LLMs can perform complex guideline-based clinical reasoning using real-world radiology reports. By combining the RECIST/AJCC criteria with structured prompts, we demonstrated how LLMs can move beyond surface-level extraction to support nuanced inference in oncology, with implications for future clinical applications.

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