Predicting Outcome of Endovascular Treatment for Acute Ischemic Stroke: Potential Value of Machine Learning Algorithms

Hendrikus J. A. van Os*, Lucas A. Ramos, Adam Hilbert, Matthijs van Leeuwen, Marianne A. A. van Walderveen, Nyika D. Kruyt, Diederik W. J. Dippel, Ewout W. Steyerberg, Irene C. van der Schaaf, Hester F. Lingsma, Wouter J. Schonewille, Charles B. L. M. Majoie, Silvia D. Olabarriaga, Koos H. Zwinderman, Esmee Venema, Henk A. Marquering, Marieke J. H. Wermer, MR CLEAN Registry Investigators, Robert Jan van Oostenbrugge, Wim van Zwam

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Original languageEnglish
Article number784
Number of pages8
JournalFrontiers in Neurology
Volume9
DOIs
Publication statusPublished - 25 Sep 2018

Keywords

  • ischemic stroke
  • prediction
  • machine learning
  • endovascular treatment
  • functional outcome
  • reperfusion
  • TRAUMATIC BRAIN-INJURY
  • BREAST-CANCER
  • SUPER LEARNER
  • REGRESSION
  • SELECTION
  • CHEMOTHERAPY
  • MODELS
  • TRIALS
  • SCORE
  • RISK

Cite this

van Os, H. J. A., Ramos, L. A., Hilbert, A., van Leeuwen, M., van Walderveen, M. A. A., Kruyt, N. D., Dippel, D. W. J., Steyerberg, E. W., van der Schaaf, I. C., Lingsma, H. F., Schonewille, W. J., Majoie, C. B. L. M., Olabarriaga, S. D., Zwinderman, K. H., Venema, E., Marquering, H. A., Wermer, M. J. H., MR CLEAN Registry Investigators, van Oostenbrugge, R. J., & van Zwam, W. (2018). Predicting Outcome of Endovascular Treatment for Acute Ischemic Stroke: Potential Value of Machine Learning Algorithms. Frontiers in Neurology, 9, [784]. https://doi.org/10.3389/fneur.2018.00784