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August 16, 2025Open Access

Deep learning-based identification of necrosis and microvascular proliferation in adult diffuse gliomas from whole-slide images

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Authors

YGYumeng GuoHHHanli HuangXLXing Liu

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Overview

Deep learning identifies necrosis and microvascular proliferation in adult diffuse gliomas, suggesting efficient histopathological analysis.

Key Points

  • Patient-level deep learning models achieved an AUC of 0.9968 and 0.9995 for necrosis and microvascular proliferation, respectively.
  • The model reached an accuracy of 88.05% for necrosis and 90.20% for microvascular proliferation compared to traditional pathology reports.
  • Utilizing datasets from 621 whole-slide images (WSIs), the framework automates the detection and quantification of key histopathological features.
  • Clustering analyses of extracted features may enhance understanding of necrosis and microvascular proliferation subtypes.

Cite This Study

Guo et al. (2025) studied this question.

synapsesocial.com/papers/68af3e49cf1dd9ea359eb4f7https://doi.org/10.1101/2025.08.14.25333656
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