{"id":"https://openalex.org/W4400031790","doi":"https://doi.org/10.1186/s13040-024-00372-2","title":"Electronic medical records imputation by temporal Generative Adversarial Network","display_name":"Electronic medical records imputation by temporal Generative Adversarial Network","publication_year":2024,"publication_date":"2024-06-26","ids":{"openalex":"https://openalex.org/W4400031790","doi":"https://doi.org/10.1186/s13040-024-00372-2","pmid":"https://pubmed.ncbi.nlm.nih.gov/38926718"},"language":"en","primary_location":{"id":"doi:10.1186/s13040-024-00372-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13040-024-00372-2","pdf_url":"https://biodatamining.biomedcentral.com/counter/pdf/10.1186/s13040-024-00372-2","source":{"id":"https://openalex.org/S84409260","display_name":"BioData Mining","issn_l":"1756-0381","issn":["1756-0381"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioData Mining","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://biodatamining.biomedcentral.com/counter/pdf/10.1186/s13040-024-00372-2","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101411081","display_name":"Yunfei Yin","orcid":"https://orcid.org/0000-0003-1792-1378"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yunfei Yin","raw_affiliation_strings":["College of Computer Science, Chongqing University, Chongqing, 400044, China. yinyunfei@cqu.edu.cn","College of Computer Science, Chongqing University, Chongqing, 400044, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, 400044, China. yinyunfei@cqu.edu.cn","institution_ids":[]},{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, 400044, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101981352","display_name":"Yuan Zheng","orcid":"https://orcid.org/0000-0002-4991-0190"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Yuan","raw_affiliation_strings":["College of Computer Science, Chongqing University, Chongqing, 400044, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, 400044, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110524800","display_name":"Islam Tanvir","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Islam Md Tanvir","raw_affiliation_strings":["College of Computer Science, Chongqing University, Chongqing, 400044, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, 400044, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042976571","display_name":"Xianjian Bao","orcid":null},"institutions":[{"id":"https://openalex.org/I184842277","display_name":"Maharishi International University","ror":"https://ror.org/00qv5rb32","country_code":"US","type":"education","lineage":["https://openalex.org/I184842277"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xianjian Bao","raw_affiliation_strings":["Department of Computer Science, Maharishi University of Management, Fairfield, IOWA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Maharishi University of Management, Fairfield, IOWA, USA","institution_ids":["https://openalex.org/I184842277"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101411081"],"corresponding_institution_ids":["https://openalex.org/I158842170"],"apc_list":{"value":1690,"currency":"GBP","value_usd":2072},"apc_paid":{"value":1690,"currency":"GBP","value_usd":2072},"fwci":2.0069,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.88169411,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"17","issue":"1","first_page":"19","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9997000098228455,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10862","display_name":"AI in cancer detection","score":0.9804999828338623,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.9164135456085205},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7842413187026978},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.7503207921981812},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.609712541103363},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5825244188308716},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5506519675254822},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5344405174255371},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.5092793703079224},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.46440649032592773},{"id":"https://openalex.org/keywords/mean-absolute-percentage-error","display_name":"Mean absolute percentage error","score":0.4116554260253906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39275503158569336},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.382528156042099},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.25251471996307373},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.24198025465011597},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.21394258737564087},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08903706073760986}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.9164135456085205},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7842413187026978},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.7503207921981812},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.609712541103363},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5825244188308716},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5506519675254822},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5344405174255371},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.5092793703079224},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.46440649032592773},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.4116554260253906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39275503158569336},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.382528156042099},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.25251471996307373},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.24198025465011597},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.21394258737564087},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08903706073760986},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1186/s13040-024-00372-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13040-024-00372-2","pdf_url":"https://biodatamining.biomedcentral.com/counter/pdf/10.1186/s13040-024-00372-2","source":{"id":"https://openalex.org/S84409260","display_name":"BioData Mining","issn_l":"1756-0381","issn":["1756-0381"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioData Mining","raw_type":"journal-article"},{"id":"pmid:38926718","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38926718","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioData mining","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11202349","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11202349","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11202349/pdf/13040_2024_Article_372.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BioData Min","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:717967e9ad3c47dd8820348daaa9d5ef","is_oa":true,"landing_page_url":"https://doaj.org/article/717967e9ad3c47dd8820348daaa9d5ef","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BioData Mining, Vol 17, Iss 1, Pp 1-22 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s13040-024-00372-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13040-024-00372-2","pdf_url":"https://biodatamining.biomedcentral.com/counter/pdf/10.1186/s13040-024-00372-2","source":{"id":"https://openalex.org/S84409260","display_name":"BioData Mining","issn_l":"1756-0381","issn":["1756-0381"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioData Mining","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6299999952316284,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G18243275","display_name":null,"funder_award_id":"gxhiid2208","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4224768938","display_name":null,"funder_award_id":"2023CDJYGRH-YB11","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4712688190","display_name":null,"funder_award_id":"61962038","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5525479547","display_name":null,"funder_award_id":"2023CDJYGRH","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400031790.pdf"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1977924171","https://openalex.org/W2623902889","https://openalex.org/W2747845624","https://openalex.org/W2803805253","https://openalex.org/W2898711771","https://openalex.org/W2900772899","https://openalex.org/W2912306800","https://openalex.org/W2918051096","https://openalex.org/W2952267276","https://openalex.org/W2994660581","https://openalex.org/W3004008526","https://openalex.org/W3007192638","https://openalex.org/W3010598465","https://openalex.org/W3013611019","https://openalex.org/W3045312989","https://openalex.org/W3148784668","https://openalex.org/W3174697924","https://openalex.org/W3183848791","https://openalex.org/W3191689323","https://openalex.org/W3196402958","https://openalex.org/W3199528859","https://openalex.org/W3208488696","https://openalex.org/W3214589801","https://openalex.org/W4200485621","https://openalex.org/W4200627953","https://openalex.org/W4214812426","https://openalex.org/W4221120819","https://openalex.org/W4226254502","https://openalex.org/W4256708289","https://openalex.org/W4290996603","https://openalex.org/W4323350499","https://openalex.org/W6703235301"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W2055961818","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W3028371478","https://openalex.org/W2081476516","https://openalex.org/W2581984549"],"abstract_inverted_index":{"The":[0,131,150],"loss":[1],"of":[2,12,43,61,73,142],"electronic":[3,44,175],"medical":[4,45,176],"records":[5],"has":[6],"seriously":[7],"affected":[8],"the":[9,40,58,71,77,84,92,125,128,137,145,156,160,170,186,192],"practical":[10],"application":[11],"biomedical":[13,184],"data.":[14,27],"Therefore,":[15],"it":[16,107],"is":[17,133,152],"a":[18],"meaningful":[19],"research":[20,180],"effort":[21],"to":[22,38,69,111,119,135,154],"effectively":[23],"fill":[24,39],"these":[25,62],"lost":[26],"Currently,":[28],"state-of-the-art":[29,194],"methods":[30,63],"focus":[31],"on":[32,163,181],"using":[33,109],"Generative":[34,95],"Adversarial":[35,96],"Networks":[36],"(GANs)":[37],"missing":[41,56],"values":[42,114],"records,":[46],"achieving":[47],"breakthrough":[48],"progress.":[49],"However,":[50],"when":[51],"facing":[52],"datasets":[53],"with":[54,196],"high":[55],"rates,":[57],"imputation":[59,79,113],"accuracy":[60],"sharply":[64],"deceases.":[65],"This":[66],"motivates":[67],"us":[68],"explore":[70],"uncertainty":[72,141],"GANs":[74],"and":[75,91,100,115,127,140,147,204],"improve":[76],"GAN-based":[78],"methods.":[80],"In":[81,105],"this":[82],"paper,":[83],"GRUD":[85,118,129,161],"(Gate":[86],"Recurrent":[87],"Unit":[88],"Decay)":[89],"network":[90],"UGAN":[93,126],"(Uncertainty":[94],"Network)":[97],"are":[98],"proposed":[99],"organically":[101],"combined,":[102],"called":[103],"UGAN-GRUD.":[104],"UGAN-GRUD,":[106],"highlights":[108],"GAN":[110],"generate":[112],"then":[116],"leveraging":[117,159],"compensate":[120,155],"them.":[121],"We":[122],"have":[123],"designed":[124],"network.":[130],"former":[132,157],"employed":[134],"learn":[136,169],"distribution":[138],"pattern":[139],"data":[143],"through":[144],"Generator":[146],"Discriminator,":[148],"iteratively.":[149],"latter":[151],"exploited":[153],"by":[158],"based":[162],"time":[164],"decay":[165],"factor,":[166],"which":[167],"can":[168],"specific":[171],"temporal":[172],"relations":[173],"in":[174],"records.":[177],"Through":[178],"experimental":[179],"publicly":[182],"available":[183],"datasets,":[185],"results":[187],"show":[188],"that":[189],"UGAN-GRUD":[190],"outperforms":[191],"current":[193],"methods,":[195],"average":[197],"13%":[198],"RMSE":[199],"(Root":[200],"Mean":[201],"Squared":[202],"Error)":[203,210],"24.5%":[205],"MAPE":[206],"(Mean":[207],"Absolute":[208],"Percentage":[209],"improvements.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
