MRI-derived deep learning models for predicting 1p/19q codeletion status in glioma patients: a systematic review and meta-analysis of diagnostic test accuracy studies.

Abstract

Authors

• Amir Mahmoud Ahmadzadeh
  Department of Radiology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
• Nima Broomand Lomer
  University of Pennsylvania, Philadelphia, USA. nima.broomand@gmail.com.
• Mohammad Amin Ashoobi
  Guilan University of Medical Sciences, Rasht, Iran.
• Danial Elyassirad
  Student Research Committee, Mashhad University of Medical Sciences, Iran.
• Benyamin Gheiji
  Student Research Committee, Mashhad University of Medical Sciences, Iran.
• Mahsa Vatanparast
  Student Research Committee, Mashhad University of Medical Sciences, Iran.
• Amirhossein Rostami
  Mashhad University of Medical Sciences, Mashhad, Iran.
• Mohammad Ali Abouei Mehrizi
  Mashhad University of Medical Sciences, Mashhad, Iran.
• Azadeh Tabari
  Department of Radiology, Massachusetts General Hospital, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States.
• Girish Bathla
  Mayo Clinic Rochester, Minnesota, USA.
• Shahriar Faghani
  Mayo Clinic Artificial Intelligence Lab, Department of Radiology, Mayo Clinic, 200 1st Street, S.W., Rochester, MN, 55905, USA.

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