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Machine Learning Using Multiparametric Magnetic Resonance Imaging Radiomic Feature Analysis to Predict Ki-67 in World Health Organization Grade I Meningiomas.

Omaditya KhannaAnahita Fathi KazerooniChristopher J FarrellMichael P BaldassariTyler D AlexanderMichael J KarsyBenjamin A GreenbergerJose A GarciaChiharu SakoJames J EvansKevin D JudyDavid W AndrewsAdam E FlandersAshwini D SharanAdam P DickerWenyin ShiChristos Davatzikos
Published in: Neurosurgery (2021)
Our proposed radiomic feature analysis can be used to stratify WHO grade I meningiomas based on Ki-67 with excellent accuracy and can be applied to skull base and nonskull base tumors with similar performance achieved.
Keyphrases
  • machine learning
  • magnetic resonance imaging
  • deep learning
  • computed tomography
  • artificial intelligence
  • neoadjuvant chemotherapy
  • squamous cell carcinoma
  • big data
  • rectal cancer
  • contrast enhanced
  • locally advanced