{"id":"https://openalex.org/W4406259773","doi":"https://doi.org/10.1109/bibm62325.2024.10822593","title":"CTGGAN:A modified generative adversarial network for imbalanced CTG signal classification during labor","display_name":"CTGGAN:A modified generative adversarial network for imbalanced CTG signal classification during labor","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406259773","doi":"https://doi.org/10.1109/bibm62325.2024.10822593"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10822593","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822593","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5115839937","display_name":"Peilin Mai","orcid":null},"institutions":[{"id":"https://openalex.org/I117532281","display_name":"Guangzhou University of Chinese Medicine","ror":"https://ror.org/03qb7bg95","country_code":"CN","type":"education","lineage":["https://openalex.org/I117532281"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peilin Mai","raw_affiliation_strings":["Guangzhou University of Chinese Medicine,School of Medical Information Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou University of Chinese Medicine,School of Medical Information Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I117532281"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083479711","display_name":"Junyuan Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I117532281","display_name":"Guangzhou University of Chinese Medicine","ror":"https://ror.org/03qb7bg95","country_code":"CN","type":"education","lineage":["https://openalex.org/I117532281"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyuan Feng","raw_affiliation_strings":["Guangzhou University of Chinese Medicine,School of Medical Information Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou University of Chinese Medicine,School of Medical Information Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I117532281"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100314881","display_name":"Luoyi Li","orcid":null},"institutions":[{"id":"https://openalex.org/I117532281","display_name":"Guangzhou University of Chinese Medicine","ror":"https://ror.org/03qb7bg95","country_code":"CN","type":"education","lineage":["https://openalex.org/I117532281"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luoyi Li","raw_affiliation_strings":["Guangzhou University of Chinese Medicine,School of Medical Information Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou University of Chinese Medicine,School of Medical Information Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I117532281"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055682121","display_name":"Qinqun Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I117532281","display_name":"Guangzhou University of Chinese Medicine","ror":"https://ror.org/03qb7bg95","country_code":"CN","type":"education","lineage":["https://openalex.org/I117532281"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinqun Chen","raw_affiliation_strings":["Guangzhou University of Chinese Medicine,School of Medical Information Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou University of Chinese Medicine,School of Medical Information Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I117532281"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051037307","display_name":"Guiqing Liu","orcid":"https://orcid.org/0000-0003-2913-8196"},"institutions":[{"id":"https://openalex.org/I4210105832","display_name":"First Affiliated Hospital of Guangzhou University of Chinese Medicine","ror":"https://ror.org/01mxpdw03","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210105832"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guiqing Liu","raw_affiliation_strings":["Guangzhou University of Chinese Medicine,The First Affiliated Hospital,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou University of Chinese Medicine,The First Affiliated Hospital,Guangzhou,China","institution_ids":["https://openalex.org/I4210105832"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101959506","display_name":"Hang Wei","orcid":"https://orcid.org/0000-0002-1820-1949"},"institutions":[{"id":"https://openalex.org/I117532281","display_name":"Guangzhou University of Chinese Medicine","ror":"https://ror.org/03qb7bg95","country_code":"CN","type":"education","lineage":["https://openalex.org/I117532281"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Wei","raw_affiliation_strings":["Guangzhou University of Chinese Medicine,School of Medical Information Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou University of Chinese Medicine,School of Medical Information Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I117532281"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5001","last_page":"5008"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12935","display_name":"Healthcare Systems and Public Health","score":0.8205999732017517,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T12935","display_name":"Healthcare Systems and Public Health","score":0.8205999732017517,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T13248","display_name":"Healthcare Technology and Patient Monitoring","score":0.7160999774932861,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/adversarial-system","display_name":"Adversarial system","score":0.7847837805747986},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.716576874256134},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5975455045700073},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5197595953941345},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5146318674087524},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39166587591171265},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3529236316680908}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7847837805747986},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.716576874256134},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5975455045700073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5197595953941345},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5146318674087524},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39166587591171265},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3529236316680908},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm62325.2024.10822593","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822593","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.5699999928474426,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2171630164","https://openalex.org/W2591731698","https://openalex.org/W2739146657","https://openalex.org/W2804196013","https://openalex.org/W2922623974","https://openalex.org/W2995171201","https://openalex.org/W3024129096","https://openalex.org/W3064554225","https://openalex.org/W3119183218","https://openalex.org/W3130832632","https://openalex.org/W3136490428","https://openalex.org/W3169245304","https://openalex.org/W3182155274","https://openalex.org/W3209085442","https://openalex.org/W4205790295","https://openalex.org/W4210305643","https://openalex.org/W4280635833","https://openalex.org/W4295679762"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W4288019534"],"abstract_inverted_index":{"Cardiotocography":[0],"(CTG)":[1],"is":[2],"a":[3,85,111,166],"primary":[4],"tool":[5],"for":[6,38,56,204],"real-time":[7],"monitoring":[8],"fetal":[9,206],"heart":[10],"rate":[11],"(FHR)":[12],"and":[13,72,94],"uterine":[14],"contraction":[15],"(UC)":[16],"signals":[17,78,97,149],"during":[18,79,108],"labor.":[19,80],"Nowadays":[20],"CTG":[21,32,57,148,154,183],"signal":[22,70],"classification":[23,174,184],"models":[24,185],"based":[25],"on":[26,68],"deep":[27,35,58],"learning":[28],"have":[29],"facilitated":[30],"end-to-end":[31],"interpretation":[33],"through":[34],"neural":[36],"networks":[37],"automatic":[39],"feature":[40],"extraction.":[41],"However,":[42],"the":[43,74,119,134,137,158,172,178,187,199],"extreme":[44],"rarity":[45],"of":[46,76,113,136,160,190,201],"abnormal":[47,202],"cases":[48,203],"in":[49,169],"clinical":[50],"settings":[51],"has":[52],"posed":[53],"great":[54],"challenges":[55],"learning.":[59],"Meanwhile,":[60],"most":[61],"Generative":[62],"Adversarial":[63],"Network":[64],"(GAN)-based":[65],"studies":[66],"focused":[67],"FHR":[69,93],"generation":[71],"ignored":[73],"importance":[75],"UC":[77,95],"Hence,":[81],"we":[82],"introduced":[83],"CTGGAN,":[84],"modified":[86],"GAN":[87],"specifically":[88],"designed":[89],"to":[90,104,128],"simulate":[91],"both":[92],"intrapartum":[96,205],"simultaneously.":[98],"Our":[99],"approach":[100],"incorporated":[101],"Wasserstein":[102],"Distance":[103],"prevent":[105],"gradient":[106],"vanishing":[107],"training,":[109],"alongside":[110],"set":[112],"latent":[114],"code":[115],"vectors":[116],"that":[117,144,150],"enhance":[118],"generator":[120],"controllability.":[121],"We":[122],"also":[123],"integrated":[124],"an":[125],"auxiliary":[126],"classifier":[127],"impose":[129],"categorical":[130],"constraints,":[131],"thereby":[132],"enriching":[133],"diversity":[135],"generated":[138,147],"samples.":[139],"The":[140],"experimental":[141],"results":[142],"demonstrated":[143],"CTGGAN":[145,161],"effectively":[146,197],"closely":[151],"resembled":[152],"real":[153],"signals.":[155],"In":[156,193],"addition,":[157],"incorporation":[159],"significantly":[162],"improved":[163],"performance,":[164],"with":[165,180],"19.18%":[167],"increase":[168],"sensitivity":[170],"over":[171],"traditional":[173],"without":[175],"GAN.":[176],"Furthermore,":[177],"comparison":[179],"several":[181],"state-of-the-art":[182],"underscored":[186],"discriminative":[188],"performance":[189],"our":[191],"CTGGAN.":[192],"conclusion,":[194],"this":[195],"study":[196],"enhanced":[198],"detection":[200],"monitoring.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
