Localization of epileptogenic foci using artificial neural networks

Iyad E. Ouaiss, Atam P. Dhawan, Michael D. Privitera

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

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 (ROC) analysis. Results show that the Radial Basis Function Classifier yielded the most promising results although other classification techniques produced satisfactory results as well.

Original languageEnglish (US)
Pages (from-to)1121-1122
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume16
Issue numberpt 2
StatePublished - Dec 1 1994
Externally publishedYes
EventProceedings of the 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 1 (of 2) - Baltimore, MD, USA
Duration: Nov 3 1994Nov 6 1994

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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