{"id":"https://openalex.org/W4312629063","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892749","title":"Coupling Deep Imputation with Multitask Learning for Downstream Tasks on Omics Data","display_name":"Coupling Deep Imputation with Multitask Learning for Downstream Tasks on Omics Data","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312629063","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892749"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892749","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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/A5014580146","display_name":"Sophie Peacock","orcid":"https://orcid.org/0000-0002-6966-680X"},"institutions":[{"id":"https://openalex.org/I105036370","display_name":"AstraZeneca (United Kingdom)","ror":"https://ror.org/04r9x1a08","country_code":"GB","type":"company","lineage":["https://openalex.org/I105036370"]},{"id":"https://openalex.org/I4210114036","display_name":"AstraZeneca (Singapore)","ror":"https://ror.org/023p4rz42","country_code":"SG","type":"company","lineage":["https://openalex.org/I105036370","https://openalex.org/I4210114036"]},{"id":"https://openalex.org/I4210136823","display_name":"AstraZeneca (Poland)","ror":"https://ror.org/04gdybn86","country_code":"PL","type":"company","lineage":["https://openalex.org/I105036370","https://openalex.org/I4210136823"]}],"countries":["GB","PL","SG"],"is_corresponding":false,"raw_author_name":"Sophie Peacock","raw_affiliation_strings":["AstraZeneca,Cambridge,UK","AstraZeneca, Cambridge, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AstraZeneca,Cambridge,UK","institution_ids":["https://openalex.org/I4210114036","https://openalex.org/I105036370","https://openalex.org/I4210136823"]},{"raw_affiliation_string":"AstraZeneca, Cambridge, UK","institution_ids":["https://openalex.org/I105036370"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064542276","display_name":"Etai Jacob","orcid":"https://orcid.org/0009-0007-4599-0457"},"institutions":[{"id":"https://openalex.org/I4210092243","display_name":"AstraZeneca (South Korea)","ror":"https://ror.org/00h1xaa75","country_code":"KR","type":"company","lineage":["https://openalex.org/I105036370","https://openalex.org/I4210092243"]},{"id":"https://openalex.org/I4210150756","display_name":"AstraZeneca (United States)","ror":"https://ror.org/043cec594","country_code":"US","type":"company","lineage":["https://openalex.org/I105036370","https://openalex.org/I4210150756"]}],"countries":["KR","US"],"is_corresponding":false,"raw_author_name":"Etai Jacob","raw_affiliation_strings":["AstraZeneca,Waltham,USA","AstraZeneca, Waltham, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AstraZeneca,Waltham,USA","institution_ids":["https://openalex.org/I4210092243"]},{"raw_affiliation_string":"AstraZeneca, Waltham, USA","institution_ids":["https://openalex.org/I4210150756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039540762","display_name":"Nikolay Burlutskiy","orcid":null},"institutions":[{"id":"https://openalex.org/I105036370","display_name":"AstraZeneca (United Kingdom)","ror":"https://ror.org/04r9x1a08","country_code":"GB","type":"company","lineage":["https://openalex.org/I105036370"]},{"id":"https://openalex.org/I4210114036","display_name":"AstraZeneca (Singapore)","ror":"https://ror.org/023p4rz42","country_code":"SG","type":"company","lineage":["https://openalex.org/I105036370","https://openalex.org/I4210114036"]},{"id":"https://openalex.org/I4210136823","display_name":"AstraZeneca (Poland)","ror":"https://ror.org/04gdybn86","country_code":"PL","type":"company","lineage":["https://openalex.org/I105036370","https://openalex.org/I4210136823"]}],"countries":["GB","PL","SG"],"is_corresponding":false,"raw_author_name":"Nikolay Burlutskiy","raw_affiliation_strings":["AstraZeneca,Cambridge,UK","AstraZeneca, Cambridge, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AstraZeneca,Cambridge,UK","institution_ids":["https://openalex.org/I4210114036","https://openalex.org/I105036370","https://openalex.org/I4210136823"]},{"raw_affiliation_string":"AstraZeneca, Cambridge, UK","institution_ids":["https://openalex.org/I105036370"]}]}],"institutions":[],"countries_distinct_count":5,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1608,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.91176471,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9945999979972839,"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/T10062","display_name":"MicroRNA in disease regulation","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.6603783965110779},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.632100522518158},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.621797502040863},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6161949634552002},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5889664888381958},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5817331075668335},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5604628920555115},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5111399292945862},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.46538227796554565},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3466201424598694},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.1943162977695465},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14307904243469238},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09225204586982727}],"concepts":[{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.6603783965110779},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.632100522518158},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.621797502040863},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6161949634552002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5889664888381958},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5817331075668335},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5604628920555115},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5111399292945862},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.46538227796554565},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3466201424598694},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.1943162977695465},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14307904243469238},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09225204586982727},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892749","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1959608418","https://openalex.org/W2095705004","https://openalex.org/W2096863518","https://openalex.org/W2101234009","https://openalex.org/W2126293923","https://openalex.org/W2162772535","https://openalex.org/W2167205245","https://openalex.org/W2181255501","https://openalex.org/W2807563096","https://openalex.org/W2891816174","https://openalex.org/W2892313722","https://openalex.org/W2908055926","https://openalex.org/W2913340405","https://openalex.org/W2944016032","https://openalex.org/W2950235747","https://openalex.org/W2951209146","https://openalex.org/W2963243933","https://openalex.org/W2985928856","https://openalex.org/W3025133004","https://openalex.org/W3040723250","https://openalex.org/W3095135394","https://openalex.org/W3133956427","https://openalex.org/W3176966473","https://openalex.org/W3188230674","https://openalex.org/W4230030715","https://openalex.org/W6631190155","https://openalex.org/W6640963894","https://openalex.org/W6674330103","https://openalex.org/W6675354045"],"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":{"Omics":[0],"data":[1,44,47,53,72,102,144],"such":[2],"as":[3,48],"RNA":[4,10,127],"gene":[5],"expression,":[6],"methylation":[7],"and":[8,33,128,159],"micro":[9,126],"expression":[11],"are":[12,69,195],"valuable":[13],"sources":[14,54],"of":[15,165,190],"information":[16,37],"for":[17,56,145,174,200],"various":[18],"clinical":[19,43],"predictive":[20,202],"tasks.":[21,203],"For":[22],"example,":[23],"predicting":[24],"survival":[25,175],"outcomes,":[26],"response":[27],"to":[28,76,90,115,137],"drugs,":[29],"cancer":[30],"histology":[31],"type":[32],"other":[34],"patients":[35],"related":[36],"is":[38],"possible":[39],"using":[40,51,106,120,170],"not":[41],"only":[42],"but":[45],"molecular":[46],"well.":[49],"Moreover,":[50],"these":[52],"together,":[55],"example":[57],"in":[58,66,86,157],"multitask":[59,111,155,180],"learning,":[60],"might":[61],"boost":[62],"the":[63],"performance.":[64],"However,":[65],"practice,":[67],"there":[68],"many":[70],"missing":[71,104],"points":[73],"which":[74,85],"leads":[75],"significantly":[77,184],"lower":[78],"patient":[79,142],"numbers":[80],"when":[81,169,197],"analysing":[82],"full":[83],"cases,":[84],"our":[87],"setting":[88],"refers":[89],"all":[91,171],"modalities":[92,123,173],"being":[93],"present.":[94],"In":[95,167],"this":[96],"paper":[97],"we":[98,177],"investigate":[99],"how":[100],"imputing":[101],"with":[103,110],"values":[105,139],"deep":[107,134,150,186],"learning":[108,112,156,181],"coupled":[109],"can":[113],"help":[114],"reach":[116],"state-of-the-art":[117],"performance":[118,199],"results":[119],"combined":[121],"omics":[122],"-":[124],"RNA,":[125],"methylation.":[129],"We":[130],"propose":[131],"a":[132,141],"generalised":[133],"imputation":[135,151,187],"method":[136],"impute":[138],"where":[140],"has":[143],"one":[146],"modality":[147],"missing.":[148],"Interestingly,":[149],"by":[152,182],"itself":[153,183],"outperforms":[154,185],"classification":[158],"regression":[160],"tasks":[161],"across":[162],"most":[163],"combinations":[164],"modalities.":[166],"contrast,":[168],"available":[172],"prediction":[176],"observe":[178],"that":[179],"(adjusted":[188],"p-value":[189],"0.03).":[191],"Thus,":[192],"both":[193],"approaches":[194],"complementary":[196],"optimising":[198],"downstream":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-14T07:44:22.658603","created_date":"2025-10-10T00:00:00"}