Seizure prediction based on features extracted from electrocorticogram recordings can be achieved with both high selectivity and specificity. This chapter will provide a review of the basics for developing a seizure prediction algorithm, utilizing feature selection, classification training, evaluation, and subsequent optimization.
|Original language||English (US)|
|Title of host publication||Engineering in Medicine|
|Subtitle of host publication||Advances and Challenges|
|Number of pages||14|
|State||Published - Jan 1 2018|
- Machine learning