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In this work, the epilepsy detection task is approached in two different ways, recurrent and convolutional neural networks, within a patient-specific scheme. Additionally, a detector function and its effects on seizure detection performance are presented. Our results suggest that it is possible to detect seizures from scalp EEGs with acceptable results for some patients, and that the DeepHealth framework is a proper deep learning software for medical research.<\/jats:p>","DOI":"10.1007\/978-3-031-13321-3_46","type":"book-chapter","created":{"date-parts":[[2022,8,6]],"date-time":"2022-08-06T17:03:55Z","timestamp":1659805435000},"page":"522-532","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Automatic Detection of\u00a0Epileptic Seizures with\u00a0Recurrent and\u00a0Convolutional Neural Networks"],"prefix":"10.1007","author":[{"given":"Salvador","family":"Carri\u00f3n","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"\u00c1lvaro","family":"L\u00f3pez-Chilet","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Javier","family":"Mart\u00ednez-Bernia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joan","family":"Coll-Alonso","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Chorro-Juan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jon Ander","family":"G\u00f3mez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,8,7]]},"reference":[{"key":"46_CR1","doi-asserted-by":"publisher","unstructured":"Ahmed, A., Magdy, B.: A deep learning approach for automatic seizure detection in children with epilepsy. 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