@inproceedings{24dcd76ed23b4329be02e3a1600eb2f4,
title = "Impact of personalization on epileptic seizure prediction",
abstract = "The main contribution of this paper is a personalization method which systematically selects the algorithm's parameters based on patient's individual data. The conventional seizure prediction techniques use a fixed set of parameters (like window size and time-to-seizure of preictal data). In this work, we report how personalizing the preictal data parameters improves the quality of seizure prediction. Experimental results show that using a personalized small set of parameters increase the F-measure accuracy of seizure prediction.",
keywords = "EEG, Epileptic Seizure, Parameter Assessment, Personalization, Seizure Prediction",
author = "Javad Birjandtalab and Jarmale, {Vipul Nataraj} and Mehrdad Nourani and Jay Harvey",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 ; Conference date: 19-05-2019 Through 22-05-2019",
year = "2019",
month = may,
doi = "10.1109/BHI.2019.8834648",
language = "English (US)",
series = "2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings",
}