{"id":"https://openalex.org/W3030713386","doi":"https://doi.org/10.1145/3383972.3384053","title":"Intracranial Electroencephalogram Based Epilepsy Seizure Onset Detection","display_name":"Intracranial Electroencephalogram Based Epilepsy Seizure Onset Detection","publication_year":2020,"publication_date":"2020-02-15","ids":{"openalex":"https://openalex.org/W3030713386","doi":"https://doi.org/10.1145/3383972.3384053","mag":"3030713386"},"language":"en","primary_location":{"id":"doi:10.1145/3383972.3384053","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3383972.3384053","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 12th International Conference on Machine Learning and Computing","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/A5045439927","display_name":"Boyu Fan","orcid":"https://orcid.org/0000-0002-1743-5225"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Boyu Fan","raw_affiliation_strings":["Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101746187","display_name":"Jiaming Xu","orcid":"https://orcid.org/0000-0001-7635-1059"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiaming Xu","raw_affiliation_strings":["Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102361287","display_name":"Xujie Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xujie Zhang","raw_affiliation_strings":["Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5045439927"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1116,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.40916582,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"368","last_page":"372"},"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/T10094","display_name":"Epilepsy research and treatment","score":0.9961000084877014,"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"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9894999861717224,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7523959875106812},{"id":"https://openalex.org/keywords/epilepsy","display_name":"Epilepsy","score":0.73777836561203},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6448892951011658},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6310957670211792},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.5730912089347839},{"id":"https://openalex.org/keywords/epileptic-seizure","display_name":"Epileptic seizure","score":0.5466287136077881},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5134881138801575},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4168750047683716},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41320380568504333},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40437400341033936},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.152561753988266},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.14539870619773865}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7523959875106812},{"id":"https://openalex.org/C2778186239","wikidata":"https://www.wikidata.org/wiki/Q41571","display_name":"Epilepsy","level":2,"score":0.73777836561203},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6448892951011658},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6310957670211792},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.5730912089347839},{"id":"https://openalex.org/C2779334592","wikidata":"https://www.wikidata.org/wiki/Q6279182","display_name":"Epileptic seizure","level":3,"score":0.5466287136077881},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5134881138801575},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4168750047683716},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41320380568504333},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40437400341033936},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.152561753988266},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.14539870619773865}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3383972.3384053","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3383972.3384053","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 12th International Conference on Machine Learning and Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.5099999904632568,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1974267840","https://openalex.org/W1983297775","https://openalex.org/W1995232709","https://openalex.org/W2022437153","https://openalex.org/W2024580832","https://openalex.org/W2041295646","https://openalex.org/W2052032553","https://openalex.org/W2143776609","https://openalex.org/W2152147396","https://openalex.org/W2415653778","https://openalex.org/W2527824850","https://openalex.org/W2776032868","https://openalex.org/W2994140328","https://openalex.org/W4323285610","https://openalex.org/W6656071679"],"related_works":["https://openalex.org/W2395385109","https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W2773633178","https://openalex.org/W3171520305","https://openalex.org/W2889302474","https://openalex.org/W2166624857","https://openalex.org/W2363907062","https://openalex.org/W2393137063"],"abstract_inverted_index":{"Epilepsy":[0],"is":[1],"a":[2,89],"neural":[3],"disorder":[4],"affecting":[5],"39":[6],"million":[7],"people":[8],"around":[9],"the":[10,14,52,55,64,72,101,107,120],"world.":[11],"Recently,":[12],"with":[13],"rapid":[15],"growth":[16],"of":[17,29,54,92,103],"applying":[18],"machine":[19],"learning":[20],"models":[21],"to":[22],"biomedical":[23],"data,":[24],"Electroencephalogram":[25,41],"has":[26],"proven":[27],"capable":[28],"detecting":[30],"epilepsy":[31],"seizure":[32,44],"onset.":[33],"In":[34],"this":[35,68,124],"work,":[36],"we":[37,80],"introduce":[38],"an":[39],"intracranial":[40],"(iEEG)":[42],"-based":[43],"detection":[45],"algorithm.":[46],"This":[47],"method":[48],"relies":[49],"on":[50,75,85],"exploits":[51],"advantage":[53],"high-frequency":[56],"components":[57],"embedded":[58],"in":[59],"iEEG":[60],"signals.":[61],"We":[62,70,98],"select":[63],"optimum":[65],"classifier":[66,122],"for":[67,123],"task.":[69,125],"test":[71],"algorithm":[73],"performance":[74,109],"three":[76],"patients.":[77],"On":[78],"average,":[79],"achieve":[81],"over":[82],"99%":[83],"accuracy":[84],"1s-long":[86],"windows":[87],"and":[88,110],"F1":[90],"score":[91],"94%":[93],"(for":[94],"measuring":[95],"imbalanced":[96],"data).":[97],"also":[99],"analyzed":[100],"complexity":[102],"different":[104],"classifiers.":[105],"Taking":[106],"classification":[108],"power":[111],"consumption":[112],"into":[113],"consideration,":[114],"gradient":[115],"boosted":[116],"decision":[117],"trees":[118],"present":[119],"best":[121]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}