Weakly supervised language models for automated extraction of critical findings from radiology reports

Abstract Critical findings in radiology reports are life threatening conditions that need to be communicated promptly to physicians for timely management of patients. Although challenging, advancements in natural language processing (NLP), particularly large language models (LLMs), now enable the au...

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Bibliographic Details
Main Authors: Avisha Das, Ish A. Talati, Juan Manuel Zambrano Chaves, Daniel Rubin, Imon Banerjee
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-025-01522-4
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