Localization of epileptogenic foci using artificial neural networks

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dc.contributor.author Ouaiss, I.E.
dc.contributor.author Dhawan, A.P.
dc.contributor.author Privitera, M.D.
dc.date.accessioned 2017-06-22T09:42:23Z
dc.date.available 2017-06-22T09:42:23Z
dc.date.issued 2017-06-22
dc.identifier.isbn 0-7803-2050-6 en_US
dc.identifier.uri http://hdl.handle.net/10725/5813
dc.description.abstract Current neuropsychological tests based clinical methods are often difficult to interpret for localizing seizure foci in epilepsy patients. The purpose of this study is to predict with a high degree of certainty the location of the epileptogenic foci in epilepsy patients. First, neuropsychological tests data containing information thought to be relevant to the decision making process was extracted from patients' files. Next, the collected data was normalized and based on statistical analysis techniques. A set of best features was selected. These selected features were then analyzed using different classification techniques. The performance of each classifier was compared through the receiver operating characteristic analysis. Results show that the radial basis function classifier yielded the most promising results although other classification techniques produced satisfactory results as well. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.title Localization of epileptogenic foci using artificial neural networks en_US
dc.type Conference Paper / Proceeding en_US
dc.author.school SOE en_US
dc.author.idnumber 200105659 en_US
dc.author.department Electrical And Computer Engineering en_US
dc.description.embargo N/A en_US
dc.keywords Epilepsy en_US
dc.keywords Testing en_US
dc.keywords Backpropagation algorithms en_US
dc.keywords Neural networks en_US
dc.keywords Biomedical imaging en_US
dc.keywords Clustering algorithms en_US
dc.keywords Performance analysis en_US
dc.keywords Surgery en_US
dc.keywords Medical treatment en_US
dc.keywords Radial basis function networks en_US
dc.identifier.doi http://dx.doi.org/10.1109/IEMBS.1994.415353 en_US
dc.identifier.ctation Ouaiss, I. E., Dhawan, A. P., & Privitera, M. D. (1994). Localization of epileptogenic foci using artificial neural networks. In Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE (Vol. 2, pp. 1121-1122). IEEE. en_US
dc.author.email iyad.ouaiss@lau.edu.lb en_US
dc.conference.date 3-6 Nov 1994 en_US
dc.conference.place Baltimore, MD, USA en_US
dc.conference.title Proceedings of 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url http://ieeexplore.ieee.org/abstract/document/415353/ en_US
dc.author.affiliation Lebanese American University en_US

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