Detection of cerebral aneurysms using artificial intelligence: a systematic review and meta-analysis.

Journal: Journal of neurointerventional surgery
PMID: 36375834

Abstract

BACKGROUND: Subarachnoid hemorrhage from cerebral aneurysm rupture is a major cause of morbidity and mortality. Early aneurysm identification, aided by automated systems, may improve patient outcomes. Therefore, a systematic review and meta-analysis of the diagnostic accuracy of artificial intelligence (AI) algorithms in detecting cerebral aneurysms using CT, MRI or DSA was performed.

Authors

  • Munaib Din
    School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Siddharth Agarwal
    School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom.
  • Mariusz Grzeda
    School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • David A Wood
    School of Biomedical Engineering & Imaging Sciences, Kings College London, Rayne Institute, 4th Floor, Lambeth Wing, London, SE1 7EH, UK.
  • Marc Modat
    Centre for Medical Image Computing (CMIC), Departments of Medical Physics & Biomedical Engineering and Computer Science, University College London, UK.
  • Thomas C Booth
    School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, United Kingdom.

Keywords

External Resources

Popular Topics
Recent Journals