{"id":"https://openalex.org/W4390992303","doi":"https://doi.org/10.1109/bibm58861.2023.10385362","title":"Neonatal seizure detection combined deep network and meta-learning","display_name":"Neonatal seizure detection combined deep network and meta-learning","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4390992303","doi":"https://doi.org/10.1109/bibm58861.2023.10385362"},"language":"en","primary_location":{"id":"doi:10.1109/bibm58861.2023.10385362","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bibm58861.2023.10385362","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5101831648","display_name":"Xueni Li","orcid":"https://orcid.org/0009-0008-8180-5324"},"institutions":[{"id":"https://openalex.org/I28006308","display_name":"Shandong Normal University","ror":"https://ror.org/01wy3h363","country_code":"CN","type":"education","lineage":["https://openalex.org/I28006308"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xueni Li","raw_affiliation_strings":["Shandong Normal University,School of Physics and Electronics,Jinan,China","School of Physics and Electronics, Shandong Normal University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Shandong Normal University,School of Physics and Electronics,Jinan,China","institution_ids":["https://openalex.org/I28006308"]},{"raw_affiliation_string":"School of Physics and Electronics, Shandong Normal University, Jinan, China","institution_ids":["https://openalex.org/I28006308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101399217","display_name":"Jie Liu","orcid":"https://orcid.org/0009-0007-4587-4595"},"institutions":[{"id":"https://openalex.org/I108688024","display_name":"Qingdao University","ror":"https://ror.org/021cj6z65","country_code":"CN","type":"education","lineage":["https://openalex.org/I108688024"]},{"id":"https://openalex.org/I4210156555","display_name":"Shandong Maternal and Child Health Hospital","ror":"https://ror.org/04ger2z06","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210156555"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Liu","raw_affiliation_strings":["Health Care Hospital Affiliated to Qingdao University,Shandong Provincial Maternal and Child,Department of Pediatric Intensive Care Unit,Jinan,China","Department of Pediatric Intensive Care Unit, Shandong Provincial Maternal and Child, Health Care Hospital Affiliated to Qingdao University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Health Care Hospital Affiliated to Qingdao University,Shandong Provincial Maternal and Child,Department of Pediatric Intensive Care Unit,Jinan,China","institution_ids":["https://openalex.org/I4210156555"]},{"raw_affiliation_string":"Department of Pediatric Intensive Care Unit, Shandong Provincial Maternal and Child, Health Care Hospital Affiliated to Qingdao University, Jinan, China","institution_ids":["https://openalex.org/I4210156555","https://openalex.org/I108688024"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100851763","display_name":"Weiwei Nie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210163399","display_name":"Shandong First Medical University","ror":"https://ror.org/05jb9pq57","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163399"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Nie","raw_affiliation_strings":["The First Affiliated Hospital of Shandong First Medical University Shandong First Medical University,Jinan,China","The First Affiliated Hospital of Shandong First Medical University Shandong First Medical University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"The First Affiliated Hospital of Shandong First Medical University Shandong First Medical University,Jinan,China","institution_ids":["https://openalex.org/I4210163399"]},{"raw_affiliation_string":"The First Affiliated Hospital of Shandong First Medical University Shandong First Medical University, Jinan, China","institution_ids":["https://openalex.org/I4210163399"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019180907","display_name":"Qi Yuan","orcid":"https://orcid.org/0000-0002-1342-3374"},"institutions":[{"id":"https://openalex.org/I28006308","display_name":"Shandong Normal University","ror":"https://ror.org/01wy3h363","country_code":"CN","type":"education","lineage":["https://openalex.org/I28006308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Yuan","raw_affiliation_strings":["Shandong Normal University,School of Physics and Electronics,Jinan,China","School of Physics and Electronics, Shandong Normal University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Shandong Normal University,School of Physics and Electronics,Jinan,China","institution_ids":["https://openalex.org/I28006308"]},{"raw_affiliation_string":"School of Physics and Electronics, Shandong Normal University, Jinan, China","institution_ids":["https://openalex.org/I28006308"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101831648"],"corresponding_institution_ids":["https://openalex.org/I28006308"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31984566,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2522","last_page":"2526"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11184","display_name":"Neonatal and fetal brain pathology","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11184","display_name":"Neonatal and fetal brain pathology","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child 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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9879999756813049,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9695000052452087,"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":0.7824880480766296},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6989679336547852},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6555022597312927},{"id":"https://openalex.org/keywords/neonatal-intensive-care-unit","display_name":"Neonatal intensive care unit","score":0.6309369802474976},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6057822108268738},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.6029187440872192},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5996934771537781},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.566364049911499},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.5579921007156372},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5548641085624695},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4853881597518921},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.41966375708580017},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.14608651399612427},{"id":"https://openalex.org/keywords/pediatrics","display_name":"Pediatrics","score":0.09378516674041748},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08644652366638184}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7824880480766296},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6989679336547852},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6555022597312927},{"id":"https://openalex.org/C2777091541","wikidata":"https://www.wikidata.org/wiki/Q9008292","display_name":"Neonatal intensive care unit","level":2,"score":0.6309369802474976},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6057822108268738},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.6029187440872192},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5996934771537781},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.566364049911499},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5579921007156372},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5548641085624695},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4853881597518921},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.41966375708580017},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.14608651399612427},{"id":"https://openalex.org/C187212893","wikidata":"https://www.wikidata.org/wiki/Q123028","display_name":"Pediatrics","level":1,"score":0.09378516674041748},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08644652366638184},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm58861.2023.10385362","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bibm58861.2023.10385362","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.5,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1974991504","https://openalex.org/W2588128256","https://openalex.org/W2795691199","https://openalex.org/W2810030448","https://openalex.org/W2990430870","https://openalex.org/W3090660492","https://openalex.org/W3152251327","https://openalex.org/W3217550076","https://openalex.org/W4200040232","https://openalex.org/W4200403066","https://openalex.org/W4206735071","https://openalex.org/W4281781592","https://openalex.org/W4284989976","https://openalex.org/W4372259834"],"related_works":["https://openalex.org/W1999699871","https://openalex.org/W4225124612","https://openalex.org/W2043806667","https://openalex.org/W2786391746","https://openalex.org/W2021633306","https://openalex.org/W2006801911","https://openalex.org/W2033669961","https://openalex.org/W2971899271","https://openalex.org/W1972167985","https://openalex.org/W1990237101"],"abstract_inverted_index":{"Neonatal":[0],"seizure":[1],"is":[2,19,65,104],"a":[3,48,77],"common":[4],"neurological":[5],"emergency":[6],"in":[7,95,113,131],"the":[8,25,51,71,90,93,110,114,117,123,132,136,140],"neonatal":[9,15],"intensive":[10,43],"care":[11],"unit":[12],"(NICU).":[13],"Automatic":[14],"epilepsy":[16],"detection":[17,72],"technology":[18],"of":[20,86,92,139,144],"great":[21],"significance":[22],"to":[23,46,67,122],"reducing":[24],"diagnosis":[26],"pressure":[27],"on":[28],"doctors":[29],"and":[30,57,69,135,147],"helping":[31],"newborns":[32],"get":[33],"timely":[34],"treatment.":[35],"Compared":[36],"with":[37,81,109],"deep":[38],"learning":[39],"models":[40],"that":[41],"require":[42],"data":[44,56],"training":[45,84,97,108],"achieve":[47],"better":[49],"result,":[50],"meta-learning":[52,87],"model":[53,64,79,94,103,118],"requires":[54],"fewer":[55],"can":[58,119],"quickly":[59,120],"fit":[60],"different":[61],"tasks.":[62],"Our":[63],"simple":[66,107],"implement":[68],"shortens":[70],"time.":[73],"Here,":[74],"we":[75],"propose":[76],"1D-CNN":[78],"trained":[80],"meta-learning.":[82],"The":[83],"method":[85],"constantly":[88],"adjusts":[89],"weight":[91,102],"several":[96],"tasks":[98],"until":[99],"an":[100],"optimal":[101],"achieved.":[105],"After":[106],"support":[111],"set":[112,125],"test":[115],"task,":[116],"adapt":[121],"query":[124],"data.":[126],"It":[127],"has":[128],"been":[129],"verified":[130],"infant":[133],"database,":[134],"average":[137],"results":[138],"three":[141],"evaluation":[142],"indicators":[143],"sensitivity,":[145],"specificity,":[146],"F1":[148],"value":[149],"exceeded":[150],"92.63%.":[151]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}