{"id":"https://openalex.org/W3157869130","doi":"https://doi.org/10.1109/iscas51556.2021.9401347","title":"An Efficient Deep Learning System for Epileptic Seizure Prediction","display_name":"An Efficient Deep Learning System for Epileptic Seizure Prediction","publication_year":2021,"publication_date":"2021-04-27","ids":{"openalex":"https://openalex.org/W3157869130","doi":"https://doi.org/10.1109/iscas51556.2021.9401347","mag":"3157869130"},"language":"en","primary_location":{"id":"doi:10.1109/iscas51556.2021.9401347","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas51556.2021.9401347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022275925","display_name":"Ahmed Abdelhameed","orcid":"https://orcid.org/0000-0002-9970-2517"},"institutions":[{"id":"https://openalex.org/I79516672","display_name":"University of Louisiana at Lafayette","ror":"https://ror.org/01x8rc503","country_code":"US","type":"education","lineage":["https://openalex.org/I2799628689","https://openalex.org/I79516672"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ahmed M. Abdelhameed","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Louisiana, Lafayette, Louisiana, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Louisiana, Lafayette, Louisiana, USA","institution_ids":["https://openalex.org/I79516672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010023744","display_name":"Magdy Bayoumi","orcid":"https://orcid.org/0000-0002-0630-5273"},"institutions":[{"id":"https://openalex.org/I79516672","display_name":"University of Louisiana at Lafayette","ror":"https://ror.org/01x8rc503","country_code":"US","type":"education","lineage":["https://openalex.org/I2799628689","https://openalex.org/I79516672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Magdy Bayoumi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Louisiana, Lafayette, Louisiana, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Louisiana, Lafayette, Louisiana, USA","institution_ids":["https://openalex.org/I79516672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5022275925"],"corresponding_institution_ids":["https://openalex.org/I79516672"],"apc_list":null,"apc_paid":null,"fwci":1.2819,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.77489747,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.982699990272522,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10094","display_name":"Epilepsy research and treatment","score":0.9825999736785889,"subfield":{"id":"https://openalex.org/subfields/2738","display_name":"Psychiatry and Mental health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.845140814781189},{"id":"https://openalex.org/keywords/epilepsy","display_name":"Epilepsy","score":0.7790704369544983},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7194793224334717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6838023066520691},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6765056848526001},{"id":"https://openalex.org/keywords/epileptic-seizure","display_name":"Epileptic seizure","score":0.6630327701568604},{"id":"https://openalex.org/keywords/ictal","display_name":"Ictal","score":0.6412725448608398},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5614458918571472},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5328325033187866},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47120043635368347},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46305322647094727},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45805370807647705},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.19579026103019714},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.18083125352859497}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.845140814781189},{"id":"https://openalex.org/C2778186239","wikidata":"https://www.wikidata.org/wiki/Q41571","display_name":"Epilepsy","level":2,"score":0.7790704369544983},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7194793224334717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6838023066520691},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6765056848526001},{"id":"https://openalex.org/C2779334592","wikidata":"https://www.wikidata.org/wiki/Q6279182","display_name":"Epileptic seizure","level":3,"score":0.6630327701568604},{"id":"https://openalex.org/C17755696","wikidata":"https://www.wikidata.org/wiki/Q16564780","display_name":"Ictal","level":3,"score":0.6412725448608398},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5614458918571472},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5328325033187866},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47120043635368347},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46305322647094727},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45805370807647705},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.19579026103019714},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.18083125352859497},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas51556.2021.9401347","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas51556.2021.9401347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1510056001","https://openalex.org/W1556131344","https://openalex.org/W1836465849","https://openalex.org/W1959608418","https://openalex.org/W1979324912","https://openalex.org/W2000690216","https://openalex.org/W2065454702","https://openalex.org/W2110661716","https://openalex.org/W2534582782","https://openalex.org/W2556806401","https://openalex.org/W2575693046","https://openalex.org/W2605817454","https://openalex.org/W2611396605","https://openalex.org/W2750384459","https://openalex.org/W2759483166","https://openalex.org/W2766958857","https://openalex.org/W2780723646","https://openalex.org/W2797694788","https://openalex.org/W2799610518","https://openalex.org/W2883540729","https://openalex.org/W2907364298","https://openalex.org/W2910917652","https://openalex.org/W2921691756","https://openalex.org/W2937349975","https://openalex.org/W2949117887","https://openalex.org/W2960026766","https://openalex.org/W2967087414","https://openalex.org/W2990556435","https://openalex.org/W3008297566","https://openalex.org/W6633205339","https://openalex.org/W6638667902","https://openalex.org/W6640963894"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2405240590","https://openalex.org/W2809907213","https://openalex.org/W3091390542","https://openalex.org/W2166624857"],"abstract_inverted_index":{"Predicting":[0],"epilepsy":[1],"ahead":[2],"of":[3,34,59,110,122,134],"its":[4],"occurrence":[5],"has":[6],"been":[7],"an":[8,119],"arduous":[9],"job":[10],"for":[11,13,47,80,100],"scientists":[12],"a":[14,24,42,87,97,107],"long":[15],"time.":[16],"Epileptic":[17],"patients":[18],"are":[19],"still":[20],"endeavoring":[21],"to":[22,27,30,112],"find":[23],"prosperous":[25],"way":[26,99],"evade":[28],"seizures":[29],"improve":[31],"the":[32,57,71,74,81,135],"quality":[33],"their":[35],"lives.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40],"propose":[41],"novel":[43],"deep":[44],"learning":[45,103],"system":[46,64,85,117],"epileptic":[48,82],"seizure":[49],"prediction":[50,108,128],"using":[51],"multi-channel":[52],"electroencephalogram":[53],"(EEG)":[54],"recordings":[55],"from":[56],"scalp":[58],"human":[60],"brains.":[61],"The":[62,84],"proposed":[63,116],"is":[65,68],"patient-specific":[66],"and":[67,76,92,104,124],"predicated":[69],"on":[70],"classification":[72],"between":[73],"interictal":[75],"preictal":[77],"brain":[78],"states":[79],"patient.":[83],"uses":[86],"two-dimensional":[88],"convolutional":[89],"variational":[90],"autoencoder":[91],"trains":[93],"it":[94,132],"once":[95],"in":[96],"supervised":[98],"automatic":[101],"feature":[102],"classification.":[105],"Within":[106],"window":[109],"up":[111],"one":[113,133],"hour,":[114],"our":[115],"achieved":[118],"average":[120,126],"sensitivity":[121],"94.45%":[123],"0.06FP/h":[125],"false":[127],"rate":[129],"which":[130],"makes":[131],"most":[136],"efficient":[137],"among":[138],"state-of-the-art":[139],"methods.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}