Current Status and Quality of Machine Learning-Based Radiomics Studies for Glioma Grading: A Systematic Review.

Journal: Oncology
Published Date: Apr 13, 2021

Abstract

INTRODUCTION: Radiomics now has significant momentum in the era of precision medicine. Glioma is one of the pathologies that has been extensively evaluated by radiomics. However, this technique has not been incorporated into clinical practice. In this systematic review, we selected and reviewed the published studies about glioma grading by radiomics to evaluate this technique's feasibility and its challenges.

Authors

  • Mohsen Tabatabaei
    Health Information Management, Office of Vice Chancellor for Research, Arak University of Medical Sciences, Arak, Iran.
  • Ali Razaei
    Department of Radiology, University of Alabama at Birmingham (UAB), Birmingham, Alabama, USA.
  • Amir Hossein Sarrami
    University of Semnan, Semnan, Iran.
  • Zahra Saadatpour
    Department of Radiology, University of Alabama at Birmingham (UAB), Birmingham, Alabama, USA.
  • Aparna Singhal
    Department of Radiology, University of Alabama at Birmingham (UAB), Birmingham, Alabama, USA.
  • Houman Sotoudeh
    Department of Radiology, University of Alabama at Birmingham (UAB), Birmingham, Alabama, USA.

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