Targeted generative data augmentation for automatic metastases detection from free-text radiology reports

Automatic identification of metastatic sites in cancer patients from electronic health records is a challenging yet crucial task with significant implications for diagnosis and treatment. In this study, we demonstrate how advancements in natural language processing, namely the instruction-following...

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Bibliographic Details
Main Authors: Maede Ashofteh Barabadi, Xiaodan Zhu, Wai Yip Chan, Amber L. Simpson, Richard K. G. Do
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Artificial Intelligence
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Online Access:https://www.frontiersin.org/articles/10.3389/frai.2025.1513674/full
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