Shareable artificial intelligence to extract cancer outcomes from electronic health records for precision oncology research

Shareable artificial intelligence to extract cancer outcomes from electronic health records for precision oncology research

Abstract Databases that link molecular data to clinical outcomes can inform precision cancer research into novel prognostic and predictive biomarkers. However, outside of clinical trials, cancer outcomes are typically recorded only in text form within electronic health records (EHRs). Artificial int...

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Main Authors: Kenneth L. Kehl, Justin Jee, Karl Pichotta, Morgan A. Paul, Pavel Trukhanov, Christopher Fong, Michele Waters, Ziad Bakouny, Wenxin Xu, Toni K. Choueiri, Chelsea Nichols, Deborah Schrag, Nikolaus Schultz
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-024-54071-x
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https://doi.org/10.1038/s41467-024-54071-x

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