Predicting prognosis and IDH mutation status for patients with lower-grade gliomas using whole slide...
Predicting prognosis and IDH mutation status for patients with lower-grade gliomas using whole slide images
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London: Nature Publishing Group UK
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English
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London: Nature Publishing Group UK
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We developed end-to-end deep learning models using whole slide images of adults diagnosed with diffusely infiltrating, World Health Organization (WHO) grade 2 gliomas to predict prognosis and the mutation status of a somatic biomarker, isocitrate dehydrogenase (IDH) 1/2. The models, which utilize ResNet-18 as a backbone, were developed and validate...
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Predicting prognosis and IDH mutation status for patients with lower-grade gliomas using whole slide images
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TN_cdi_doaj_primary_oai_doaj_org_article_f7a305b6c0774af5b9b9e09e00f7d2d9
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_f7a305b6c0774af5b9b9e09e00f7d2d9
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-021-95948-x
