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Abstract Checkpoint blockade immunotherapy is a cornerstone of lung cancer treatment, but there is a need to improve the identification of patients who will respond favorably. Here, we explored a deep learning approach to predict immunotherapy outcomes from hematoxylin and eosin (H Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 7380.
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Loo et al. (Fri,) studied this question.
www.synapsesocial.com/papers/68e72e37b6db6435876a7fa1 — DOI: https://doi.org/10.1158/1538-7445.am2024-7380
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:
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Cancer Research
Google (United States)
Enzo Life Sciences (United States)
Moog (United States)
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