| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10320546 | Artificial Intelligence in Medicine | 2014 | 10 Pages |
Abstract
Our results demonstrate that the developed methods form important ingredients for realizing a fully automatic classification of epilepsy types and can contribute to the definition of signs that are most important for the classification.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Yohannes Kassahun, Roberta Perrone, Elena De Momi, Elmar Berghöfer, Laura Tassi, Maria Paola Canevini, Roberto Spreafico, Giancarlo Ferrigno, Frank Kirchner,