Émile Lemoine, Denahin Toffa, Geneviève Pelletier-Mc Duff, An Qi Xu, Mezen Jemel, Jean-Daniel Tessier, Frédéric Lesage
, Dang K. Nguyen and Elie Bou Assi
Article (2023)
 Open Acess document in PolyPublie and at official publisher |
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Open Access to the full text of this document Terms of Use: Creative Commons Attribution Download (1MB) |
| Department: | Department of Electrical Engineering |
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| PolyPublie URL: | https://publications.polymtl.ca/54809/ |
| Journal Title: | Scientific Reports (vol. 13, no. 1) |
| Publisher: | Nature |
| DOI: | 10.1038/s41598-023-39799-8 |
| Official URL: | https://doi.org/10.1038/s41598-023-39799-8 |
| Date Deposited: | 30 Aug 2023 08:51 |
| Last Modified: | 01 Oct 2024 07:27 |
| Cite in APA 7: | Lemoine, É., Toffa, D., Pelletier-Mc Duff, G., Xu, A. Q., Jemel, M., Tessier, J.-D., Lesage, F., Nguyen, D. K., & Bou Assi, E. (2023). Machine-learning for the prediction of one-year seizure recurrence based on routine electroencephalography. Scientific Reports, 13(1), 13 pages. https://doi.org/10.1038/s41598-023-39799-8 |
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