Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/92469
DC FieldValueLanguage
dc.contributor.authorDourado, António-
dc.contributor.authorMartins, Ricardo Filipe Alves-
dc.contributor.authorDuarte, João-
dc.contributor.authorDireito, Bruno-
dc.date.accessioned2021-01-13T23:57:17Z-
dc.date.available2021-01-13T23:57:17Z-
dc.date.issued2008-
dc.identifier.isbn978-3-540-87558-1-
dc.identifier.isbn978-3-540-87559-8-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttp://hdl.handle.net/10316/92469-
dc.description.abstractSeizure prediction for untreatable epileptic patients, one of the major challenges of present neuroinformatics researchers, will allow a substantial improvement in their safety and quality of life. Neural networks, because of their plasticity and degrees of freedom, seem to be a good approach to consider the enormous variability of physiological systems. Several architectures and training algorithms are comparatively proposed in this work showing that it is possible to find an adequate network for one patient, but care must be taken to generalize to other patients. It is claimed that each patient will have his (her) own seizure prediction algorithms.pt
dc.language.isoengpt
dc.relation.ispartofseriesLecture Notes in Computer Science;-
dc.rightsopenAccesspt
dc.titleTowards Personalized Neural Networks for Epileptic Seizure Predictionpt
dc.typebookPartpt
degois.publication.firstPage479pt
degois.publication.lastPage487pt
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-540-87559-8_50pt
dc.peerreviewedyespt
dc.identifier.doi10.1007/978-3-540-87559-8_50-
degois.publication.volume5164pt
dc.date.embargo2008-01-01*
uc.date.periodoEmbargo0pt
item.grantfulltextopen-
item.languageiso639-1en-
item.fulltextCom Texto completo-
crisitem.author.orcid0000-0001-7184-185X-
Appears in Collections:FCTUC Eng.Informática - Artigos em Livros de Actas
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