Detection of Epilepsy in EEGs Using Deep Sequence Models – A Comparative Study
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-04881-4_16
Reference22 articles.
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2. Beach, R., Reading, R.: The importance of acknowledging clinical uncertainty in the diagnosis of epilepsy and non-epileptic events. Arch. Dis. Childhood 90(12), 1219–1222 (2005). https://doi.org/10.1136/adc.2004.065441
3. Benbadis, S.: The differential diagnosis of epilepsy: a critical review. Epilepsy Behav. 15(1), 15–21 (2009). https://doi.org/10.1016/j.yebeh.2009.02.024, http://dx.DOI.org/10.1016/j.yebeh.2009.02.024
4. Bongiorni, L., Balbinot, A.: Evaluation of recurrent neural networks as epileptic seizure predictor. Array 8, 100038 (2020). https://doi.org/10.1016/j.array.2020.100038
5. Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16(February 2017), 321–357 (2002). https://doi.org/10.1613/jair.953
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