ArticleNeuro-oncology advances
Interpretable artificial intelligence based determination of glioma IDH mutation status directly from histology slides.
Article in Neuro-oncology advances. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
6 authors.
Funding
Abstract
Background: Isocitrate dehydrogenase (IDH) mutation status is a diagnostic requirement for glioma with associated prognostic and therapeutic implications. Clinical routine visual assessment of tissue is insufficient to determine IDH status conclusively, mandating molecular workup that is unavailable everywhere. Methods: We developed an interpretable Artificial Intelligence (AI)-based approach for determining IDH status directly from H&E-stained glioma slides. Our study is based on 2442 multi-institutional whole slide images (WSIs) from 3 independent retrospective glioma collections, following their reclassification according to the WHO 2021 criteria: (1) TCGA-GBM/TCGA-LGG ( Results: Our approach yields AUC Conclusions: Accurate H&E-based determination of glioma IDH mutation status can expedite conclusive diagnosis and clinical decision-making and even facilitate it in underserved regions. Finally, interpretability analysis of distilled human-identifiable features can further improve our understanding of the disease.
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Registered trials
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