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Automatic Detection of Epileptic Seizures with Recurrent and Convolutional Neural Networks

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Automatic Detection of Epileptic Seizures with Recurrent and Convolutional Neural Networks

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dc.contributor.author Carrión-Ponz, Salvador es_ES
dc.contributor.author López-Chilet, Álvaro es_ES
dc.contributor.author Martínez-Bernia, Javier es_ES
dc.contributor.author Coll-Alonso, Joan es_ES
dc.contributor.author Chorro-Juan, Daniel es_ES
dc.contributor.author Gomez, J.A. es_ES
dc.date.accessioned 2024-06-06T07:00:01Z
dc.date.available 2024-06-06T07:00:01Z
dc.date.issued 2022-05-27 es_ES
dc.identifier.isbn 978-3-031-06426-5 es_ES
dc.identifier.issn 0302-9743 es_ES
dc.identifier.uri http://hdl.handle.net/10251/204754
dc.description.abstract [EN] Computer-aided diagnosis based on intelligent systems is an effective strategy to improve the efficiency of healthcare systems while reducing their costs. 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. es_ES
dc.description.sponsorship This project has received funding from the European Commission -Horizon 2020 (H2020) under the DeepHealth Project (grant agreement no 825111), and the SELENE project (grant agreement no 871467). es_ES
dc.language Inglés es_ES
dc.publisher Springer es_ES
dc.relation.ispartof 21st Internarional Conference on Image, Analysis and Processings (ICIAP 2022), Proceedings, Part I, II, III es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Deep learning es_ES
dc.subject Neural networks es_ES
dc.subject Epilepsy es_ES
dc.subject Electroencephalogram es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Automatic Detection of Epileptic Seizures with Recurrent and Convolutional Neural Networks es_ES
dc.type Comunicación en congreso es_ES
dc.type Artículo es_ES
dc.type Capítulo de libro es_ES
dc.identifier.doi 10.1007/978-3-031-13321-3_46 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/825111/EU/Deep-Learning and HPC to Boost Biomedical Applications for Health/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/871467/EU es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica es_ES
dc.description.bibliographicCitation Carrión-Ponz, S.; López-Chilet, Á.; Martínez-Bernia, J.; Coll-Alonso, J.; Chorro-Juan, D.; Gomez, J. (2022). Automatic Detection of Epileptic Seizures with Recurrent and Convolutional Neural Networks. Springer. 522-532. https://doi.org/10.1007/978-3-031-13321-3_46 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename 21st Internarional Conference on Image, Analysis and Processings (ICIAP 2022) es_ES
dc.relation.conferencedate Mayo 23-27,2022 es_ES
dc.relation.conferenceplace Lecce, Italy es_ES
dc.relation.publisherversion https://doi.org/10.1007/978-3-031-13321-3_46 es_ES
dc.description.upvformatpinicio 522 es_ES
dc.description.upvformatpfin 532 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela S\466096 es_ES
dc.contributor.funder European Commission es_ES


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