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Using Open-Source Large Language Models to Identify Access to Germline Genetic Testing in Veterans With Breast Cancer From Unstructured Text.

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Title: Using Open-Source Large Language Models to Identify Access to Germline Genetic Testing in Veterans With Breast Cancer From Unstructured Text.
Authors: Li, Chunyang1,2 (AUTHOR) Catherine.li@utah.edu, Stringer, Michael2 (AUTHOR), Patil, Vikas1,2 (AUTHOR), Mcshinsky, Richard1,2 (AUTHOR), Morreall, Deborah1,2 (AUTHOR), Yong, Christina1,2 (AUTHOR), Rasmussen, Kelli M.1,2 (AUTHOR), Burningham, Zachary1,2 (AUTHOR), Tamang, Suzanne3,4 (AUTHOR), Menendez, Carolyn S.5,6,7 (AUTHOR), Chiba, Akiko5,6,7 (AUTHOR), Moss, Haley A.5,6,7 (AUTHOR), Colonna, Sarah1,2,7,8 (AUTHOR), Rowe, Kerry7 (AUTHOR), Friedman, Daphne5,6,7 (AUTHOR), Kelley, Michael J.5,6,7 (AUTHOR), Halwani, Ahmad1,2,7,8 (AUTHOR)
Source: JCO Clinical Cancer Informatics. 7/22/2025, Vol. 9, p1-10. 10p.
Database: Academic Search Ultimate
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  Data: Using Open-Source Large Language Models to Identify Access to Germline Genetic Testing in Veterans With Breast Cancer From Unstructured Text.
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  Data: <searchLink fieldCode="JN" term="%22JCO+Clinical+Cancer+Informatics%22">JCO Clinical Cancer Informatics</searchLink>. 7/22/2025, Vol. 9, p1-10. 10p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=186778286
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