Towards Personalized Neural Networks for Epileptic Seizure Prediction



Seizure prediction for untreatable epileptic patients, one of the major challenges of present neuroinformatics researchers, will allow a substantial improvement in their safety and quality of life. Neural networks, because of their plasticity and degrees of freedom, seem to be a good approach to consider the enormous variability of physiological systems. Several architectures and training algorithms are comparatively proposed in this work showing that it is possible to find an adequate network for one patient, but care must be taken to generalize to other patients. It is claimed that each patient will have his (her) own seizure prediction algorithms


Epilepsy, data mining, seizure prediction, classification, neural networks.


neural networks; seizure prediction


International Conference on Neural Networks ICANN 2008, September 2008

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Year 2014 : 1 citations

 Design and Development of Prediction Model to Detect Seizure Activity Utilizing Higher Order Statistical Features of EEG signals. Meenakshi Sood*, and Sunil V Bhooshan
Research Journal of Pharmaceutical, Biological and Chemical Sciences, May-June 2014 p. 1129