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Biologically-informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post-treatment glioblastoma

2024-03-27

Abstract excerpt

<title>Abstract</title> <p>Intratumoral heterogeneity poses a significant challenge to the diagnosis and treatment of glioblastoma (GBM). This heterogeneity is further exacerbated during GBM recurrence, as treatment-induced reactive changes produce additional intratumoral heterogeneity that is ambiguous to differentiate on clinical imaging. There is an urgent need to develop non-invasive approaches to map the het...

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Literature Corpus work
47e19277-b2b6-58bb-abee-f53b657e1b8e
DOI
10.21203/rs.3.rs-3891425/v1
Open publication

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Biologically-informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post-treatment glioblastomaDOI 10.21203/rs.3.rs-3891425/v1
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