Machine learning for predicting post-operative outcomes in meningiomas: a systematic review and meta-analysis.

Journal: Acta neurochirurgica
Published Date:

Abstract

PURPOSE: Meningiomas are the most common primary brain tumour and account for over one-third of cases. Traditionally, estimations of morbidity and mortality following surgical resection have depended on subjective assessments of various factors, including tumour volume, location, WHO grade, extent of resection (Simpson grade) and pre-existing co-morbidities, an approach fraught with subjective variability. This systematic review and meta-analysis seeks to evaluate the efficacy with which machine learning (ML) algorithms predict post-operative outcomes in meningioma patients.

Authors

  • Siraj Y Abualnaja
    Peterborough City Hospital, Peterborough, UK.
  • James S Morris
    University of Cambridge, Cambridge, UK.
  • Hamza Rashid
    Peterborough City Hospital, Peterborough, UK.
  • William H Cook
    Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK. whc35@cam.ac.uk.
  • Adel E Helmy
    Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.