{"id":"https://openalex.org/W3197261730","doi":"https://doi.org/10.1109/jbhi.2021.3111415","title":"Choquet Integral and Coalition Game-Based Ensemble of Deep Learning Models for COVID-19 Screening From Chest X-Ray Images","display_name":"Choquet Integral and Coalition Game-Based Ensemble of Deep Learning Models for COVID-19 Screening From Chest X-Ray Images","publication_year":2021,"publication_date":"2021-09-09","ids":{"openalex":"https://openalex.org/W3197261730","doi":"https://doi.org/10.1109/jbhi.2021.3111415","mag":"3197261730","pmid":"https://pubmed.ncbi.nlm.nih.gov/34499608"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2021.3111415","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jbhi.2021.3111415","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/jbhi.2021.3111415","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Pratik Bhowal","orcid":"https://orcid.org/0000-0002-8324-0477"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Pratik Bhowal","raw_affiliation_strings":["Department of Instrumentation and Electronics Engineering, Jadavpur University, Kolkata, India"],"raw_orcid":"https://orcid.org/0000-0002-8324-0477","affiliations":[{"raw_affiliation_string":"Department of Instrumentation and Electronics Engineering, Jadavpur University, Kolkata, India","institution_ids":["https://openalex.org/I170979836"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Subhankar Sen","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Subhankar Sen","raw_affiliation_strings":["Department of Computer Science and Engineering, Manipal University, Jaipur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Manipal University, Jaipur, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jin Hee Yoon","orcid":"https://orcid.org/0000-0002-1437-1350"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jin Hee Yoon","raw_affiliation_strings":["School of Mathematics and Statistics at Sejong University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-1437-1350","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics at Sejong University, Seoul, South Korea","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zong Woo Geem","orcid":"https://orcid.org/0000-0002-0370-5562"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Zong Woo Geem","raw_affiliation_strings":["College of IT Convergence, Gachon University, Seongnam, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-0370-5562","affiliations":[{"raw_affiliation_string":"College of IT Convergence, Gachon University, Seongnam, South Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ram Sarkar","orcid":"https://orcid.org/0000-0001-8813-4086"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ram Sarkar","raw_affiliation_strings":["Department of Computer Science and Engineering, Jadavpur University, Kolkata, India"],"raw_orcid":"https://orcid.org/0000-0001-8813-4086","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Jadavpur University, Kolkata, India","institution_ids":["https://openalex.org/I170979836"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I170979836"],"apc_list":null,"apc_paid":null,"fwci":6.3093,"has_fulltext":false,"cited_by_count":56,"citation_normalized_percentile":{"value":0.97202076,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"25","issue":"12","first_page":"4328","last_page":"4339"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.949999988079071,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.949999988079071,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T13038","display_name":"Internet of Things and AI","score":0.0035000001080334187,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10041","display_name":"COVID-19 Clinical Research Studies","score":0.002899999963119626,"subfield":{"id":"https://openalex.org/subfields/2725","display_name":"Infectious Diseases"},"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/weighting","display_name":"Weighting","score":0.657800018787384},{"id":"https://openalex.org/keywords/choquet-integral","display_name":"Choquet integral","score":0.5917999744415283},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5842000246047974},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5649999976158142},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5641000270843506},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5131000280380249},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.44290000200271606},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4293999969959259}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7373999953269958},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.657800018787384},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.640999972820282},{"id":"https://openalex.org/C112799922","wikidata":"https://www.wikidata.org/wiki/Q5104911","display_name":"Choquet integral","level":3,"score":0.5917999744415283},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5842000246047974},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5824000239372253},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5649999976158142},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5641000270843506},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5131000280380249},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.44290000200271606},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4293999969959259},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.42570000886917114},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.41530001163482666},{"id":"https://openalex.org/C100516043","wikidata":"https://www.wikidata.org/wiki/Q4455138","display_name":"Fuzzy measure theory","level":5,"score":0.37860000133514404},{"id":"https://openalex.org/C178011137","wikidata":"https://www.wikidata.org/wiki/Q285997","display_name":"Dempster\u2013Shafer theory","level":2,"score":0.37369999289512634},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.36809998750686646},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3456000089645386},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.27649998664855957},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C177142836","wikidata":"https://www.wikidata.org/wiki/Q44455","display_name":"Game theory","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25130000710487366}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/jbhi.2021.3111415","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jbhi.2021.3111415","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},{"id":"pmid:34499608","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34499608","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":"IEEE journal of biomedical and health informatics","raw_type":null}],"best_oa_location":{"id":"doi:10.1109/jbhi.2021.3111415","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jbhi.2021.3111415","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W2024355048","https://openalex.org/W2031391348","https://openalex.org/W2063579700","https://openalex.org/W2063963792","https://openalex.org/W2079260212","https://openalex.org/W2117539524","https://openalex.org/W2122231878","https://openalex.org/W2144364256","https://openalex.org/W2183341477","https://openalex.org/W2275301478","https://openalex.org/W2531409750","https://openalex.org/W2752747624","https://openalex.org/W2791198783","https://openalex.org/W2898197178","https://openalex.org/W2899231248","https://openalex.org/W2941927152","https://openalex.org/W3013277995","https://openalex.org/W3019531985","https://openalex.org/W3023402713","https://openalex.org/W3025576489","https://openalex.org/W3038003980","https://openalex.org/W3048749423","https://openalex.org/W3083753334","https://openalex.org/W3085306326","https://openalex.org/W3086547236","https://openalex.org/W3087000505","https://openalex.org/W3089265909","https://openalex.org/W3132279451","https://openalex.org/W3135243128","https://openalex.org/W3144024447","https://openalex.org/W3155009271","https://openalex.org/W3155958087","https://openalex.org/W3158175401","https://openalex.org/W3163598698","https://openalex.org/W3175232474","https://openalex.org/W3180756314","https://openalex.org/W4231592989","https://openalex.org/W6604254122","https://openalex.org/W6637373629","https://openalex.org/W6726497184","https://openalex.org/W6774960221","https://openalex.org/W6776605098","https://openalex.org/W6776700526","https://openalex.org/W6779852656","https://openalex.org/W6785568974"],"related_works":[],"abstract_inverted_index":{"Under":[0],"the":[1,9,18,37,80,83,96,100,138,143,162,232,237,242,247],"present":[2],"circumstances,":[3],"when":[4],"we":[5,72,149,217],"are":[6,183,208,213],"still":[7],"under":[8],"threat":[10],"of":[11,14,39,82,88,99,132,142,164,180,202,246],"different":[12,111,178,187],"strains":[13],"coronavirus,":[15],"and":[16,30,43,156,173,194,210,236,244],"since":[17],"most":[19],"widely":[20],"used":[21],"method":[22,160],"for":[23,79,154,161],"COVID-19":[24],"detection,":[25],"RT-PCR":[26],"is":[27,47,93],"a":[28,158,220],"tedious":[29],"time-consuming":[31],"manual":[32],"procedure":[33],"with":[34,191],"poor":[35],"precision,":[36],"application":[38],"Artificial":[40],"Intelligence":[41],"(AI)":[42],"Computer-Aided":[44],"Diagnosis":[45],"(CAD)":[46],"inevitable.":[48],"Though,":[49],"some":[50,118],"vaccines":[51],"have":[52,73,109,150,218],"now":[53],"been":[54],"authorized":[55],"worldwide,":[56],"it":[57],"will":[58],"take":[59,135],"huge":[60],"time":[61],"to":[62,94],"reach":[63],"everyone,":[64],"especially":[65],"in":[66,115],"developing":[67],"countries.":[68],"In":[69,146],"this":[70,89,116,147],"work,":[71],"analyzed":[74],"Chest":[75],"X-ray":[76],"(CXR)":[77],"images":[78],"detection":[81],"coronavirus.":[84],"The":[85],"primary":[86],"agenda":[87],"proposed":[90,110,248,256],"research":[91],"study":[92],"leverage":[95],"classification":[97],"performance":[98],"deep":[101],"learning":[102,113],"models":[103],"using":[104,120,167,185],"ensemble":[105,112,155],"learning.":[106],"Many":[107],"papers":[108],"techniques":[114],"field,":[117],"methods":[119,134],"aggregation":[121],"functions":[122],"like":[123],"Weighted":[124],"Arithmetic":[125],"Mean":[126],"(WAM)":[127],"among":[128],"others.":[129],"However,":[130],"none":[131],"these":[133,199],"into":[136],"consideration":[137],"decisions":[139,212],"that":[140],"subsets":[141],"classifiers":[144],"take.":[145],"paper,":[148],"applied":[151],"Choquet":[152,206],"integral":[153],"propose":[157],"novel":[159],"evaluation":[163],"fuzzy":[165,175,181,203],"measures":[166,182],"coalition":[168,195],"game":[169,196],"theory,":[170,172],"information":[171,192],"Lambda":[174],"approximation.":[176],"Three":[177],"sets":[179,201],"calculated":[184,209],"three":[186,200,205],"weighting":[188],"schemes":[189],"along":[190],"theory":[193],"theory.":[197],"Using":[198],"measures,":[204],"integrals":[207],"their":[211],"finally":[214],"combined.":[215],"Besides,":[216],"created":[219],"database":[221],"by":[222],"combining":[223],"several":[224],"image":[225],"repositories":[226],"developed":[227,234],"recently.":[228],"Impressive":[229],"results":[230,252],"on":[231],"newly":[233],"dataset":[235,240],"challenging":[238],"COVIDx":[239],"support":[241],"efficacy":[243],"robustness":[245],"method.":[249],"Our":[250],"experimental":[251],"outperform":[253],"many":[254],"recently":[255],"methods.":[257]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2021-09-13T00:00:00"}