Electroencephalography-based machine learning models for hyperacute detection of large vessel occlusion stroke

Eva A Groenendijk, Monique Theunissen, Laura CC van Meenen, Gaby Franschman, Arjen Siegers, Marieke C Visser, Sander M van Schaik, Patricia H A Halkes, Miou S Koopman, Wouter V Potters, Henk A Marquering, Jonathan M Coutinho, Maritta N van Stigt

Open source

DOI
10.1093/esj/aakag134
Published
2026-11
Container
European Stroke Journal
Publisher
Oxford University Press (OUP)
Open access
unknown

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BibTeX

@article{allodium:10.1093/esj/aakag134,
  title = {Electroencephalography-based machine learning models for hyperacute detection of large vessel occlusion stroke},
  author = {Eva A Groenendijk and Monique Theunissen and Laura CC van Meenen and Gaby Franschman and Arjen Siegers and Marieke C Visser and Sander M van Schaik and Patricia H A Halkes and Miou S Koopman and Wouter V Potters and Henk A Marquering and Jonathan M Coutinho and Maritta N van Stigt},
  year = {2026},
  journal = {European Stroke Journal},
  doi = {10.1093/esj/aakag134},
  url = {https://doi.org/10.1093/esj/aakag134}
}

RIS

TY  - JOUR
TI  - Electroencephalography-based machine learning models for hyperacute detection of large vessel occlusion stroke
AU  - Eva A Groenendijk
AU  - Monique Theunissen
AU  - Laura CC van Meenen
AU  - Gaby Franschman
AU  - Arjen Siegers
AU  - Marieke C Visser
AU  - Sander M van Schaik
AU  - Patricia H A Halkes
AU  - Miou S Koopman
AU  - Wouter V Potters
AU  - Henk A Marquering
AU  - Jonathan M Coutinho
AU  - Maritta N van Stigt
PY  - 2026
JO  - European Stroke Journal
DO  - 10.1093/esj/aakag134
UR  - https://doi.org/10.1093/esj/aakag134
ER  - 

APA

Groenendijk, E. A., Theunissen, M., Meenen, L. C. V., Franschman, G., Siegers, A., Visser, M. C., Schaik, S. M. V., Halkes, P. H. A., Koopman, M. S., Potters, W. V., Marquering, H. A., Coutinho, J. M., & Stigt, M. N. V. (2026). Electroencephalography-based machine learning models for hyperacute detection of large vessel occlusion stroke. European Stroke Journal. https://doi.org/10.1093/esj/aakag134

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