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Using machine learning to evaluate large-scale brain networks in patients with brain tumors: Traditional and non-traditional eloquent areas.

Alexis A MorellDaniel G EichbergAshish H ShahEvan M LutherVictor M LuMichael KaderDominique M O HigginsMartin MerenzonNitesh V PatelRicardo J KomotarMichael E Ivan
Published in: Neuro-oncology advances (2022)
Our results show that large-scale brain networks are frequently affected in patients with brain tumors, even when presenting without evident neurologic deficits. In our study, the most commonly affected brain networks were related to non-traditional eloquent areas. Integrating non-invasive brain mapping machine-learning techniques into the clinical setting may help elucidate how to preserve higher-order cognitive functions associated with those networks.
Keyphrases
  • white matter
  • resting state
  • machine learning
  • cerebral ischemia
  • traumatic brain injury
  • artificial intelligence
  • mass spectrometry
  • high density