Diagnostic Accuracy of Machine Learning-Based Radiomics in Grading Gliomas: Systematic Review and Meta-Analysis.

Journal: Contrast media & molecular imaging
Published Date: Dec 18, 2020

Abstract

PURPOSE: This study aimed to estimate the diagnostic accuracy of machine learning- (ML-) based radiomics in differentiating high-grade gliomas (HGG) from low-grade gliomas (LGG) and to identify potential covariates that could affect the diagnostic accuracy of ML-based radiomic analysis in classifying gliomas.

Authors

  • Curtis K Sohn
    Queen Square Institute of Neurology, University College London, Queen Square 7, London WC1N 3BG, UK.
  • Sotirios Bisdas
    Queen Square Institute of Neurology, University College London, Queen Square 7, London WC1N 3BG, UK.

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