{"id":"https://openalex.org/W4285238125","doi":"https://doi.org/10.1109/tetci.2022.3174868","title":"AdaD-FNN for Chest CT-Based COVID-19 Diagnosis","display_name":"AdaD-FNN for Chest CT-Based COVID-19 Diagnosis","publication_year":2022,"publication_date":"2022-06-01","ids":{"openalex":"https://openalex.org/W4285238125","doi":"https://doi.org/10.1109/tetci.2022.3174868"},"language":"en","primary_location":{"id":"doi:10.1109/tetci.2022.3174868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2022.3174868","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/AdaD-FNN_for_Chest_CT-Based_COVID-19_Diagnosis/20292570","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007478332","display_name":"Xujing Yao","orcid":"https://orcid.org/0000-0001-8735-5573"},"institutions":[{"id":"https://openalex.org/I153648349","display_name":"University of Leicester","ror":"https://ror.org/04h699437","country_code":"GB","type":"education","lineage":["https://openalex.org/I153648349"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xujing Yao","raw_affiliation_strings":["School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K"],"raw_orcid":"https://orcid.org/0000-0001-8735-5573","affiliations":[{"raw_affiliation_string":"School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K","institution_ids":["https://openalex.org/I153648349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040071032","display_name":"Ziquan Zhu","orcid":"https://orcid.org/0000-0001-8792-9354"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ziquan Zhu","raw_affiliation_strings":["Science in Civil Engineering, University of Florida, Gainesville, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science in Civil Engineering, University of Florida, Gainesville, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100561302","display_name":"Cheng Kang","orcid":null},"institutions":[{"id":"https://openalex.org/I44504214","display_name":"Czech Technical University in Prague","ror":"https://ror.org/03kqpb082","country_code":"CZ","type":"education","lineage":["https://openalex.org/I44504214"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Cheng Kang","raw_affiliation_strings":["Department of Cybernetics and Robotics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Cybernetics and Robotics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic","institution_ids":["https://openalex.org/I44504214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077268657","display_name":"Shuihua Wang","orcid":"https://orcid.org/0000-0003-2238-6808"},"institutions":[{"id":"https://openalex.org/I153648349","display_name":"University of Leicester","ror":"https://ror.org/04h699437","country_code":"GB","type":"education","lineage":["https://openalex.org/I153648349"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shui-Hua Wang","raw_affiliation_strings":["School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K"],"raw_orcid":"https://orcid.org/0000-0003-2238-6808","affiliations":[{"raw_affiliation_string":"School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K","institution_ids":["https://openalex.org/I153648349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011354002","display_name":"J. M. G\u00f3rriz","orcid":"https://orcid.org/0000-0001-7069-1714"},"institutions":[{"id":"https://openalex.org/I173304897","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449","country_code":"ES","type":"education","lineage":["https://openalex.org/I173304897"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Juan Manuel Gorriz","raw_affiliation_strings":["Department of Signal Theory, Networking and Communications, University of Granada, Granada, Spain"],"raw_orcid":"https://orcid.org/0000-0001-7069-1714","affiliations":[{"raw_affiliation_string":"Department of Signal Theory, Networking and Communications, University of Granada, Granada, Spain","institution_ids":["https://openalex.org/I173304897"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100434437","display_name":"Yudong Zhang","orcid":"https://orcid.org/0000-0002-4870-1493"},"institutions":[{"id":"https://openalex.org/I153648349","display_name":"University of Leicester","ror":"https://ror.org/04h699437","country_code":"GB","type":"education","lineage":["https://openalex.org/I153648349"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yu-Dong Zhang","raw_affiliation_strings":["School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K"],"raw_orcid":"https://orcid.org/0000-0002-4870-1493","affiliations":[{"raw_affiliation_string":"School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K","institution_ids":["https://openalex.org/I153648349"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.8804,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.94186891,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"7","issue":"1","first_page":"5","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":1.0,"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":1.0,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9840999841690063,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9599999785423279,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/preprocessor","display_name":"Preprocessor","score":0.7342082858085632},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7334812879562378},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6123791933059692},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5725582242012024},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.5538700819015503},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4708877205848694},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4537737965583801},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4373045861721039},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41516417264938354},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.21264132857322693},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.16051119565963745},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.1162184476852417}],"concepts":[{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7342082858085632},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7334812879562378},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6123791933059692},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5725582242012024},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.5538700819015503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4708877205848694},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4537737965583801},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4373045861721039},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41516417264938354},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.21264132857322693},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.16051119565963745},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.1162184476852417},{"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/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tetci.2022.3174868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2022.3174868","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:figshare.com:article/20292570","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/AdaD-FNN_for_Chest_CT-Based_COVID-19_Diagnosis/20292570","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":"","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/20292570","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/AdaD-FNN_for_Chest_CT-Based_COVID-19_Diagnosis/20292570","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":"","raw_type":"Text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8299999833106995,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W20713475","https://openalex.org/W2023438527","https://openalex.org/W2088672213","https://openalex.org/W2101544546","https://openalex.org/W2101859081","https://openalex.org/W2133319764","https://openalex.org/W2189120710","https://openalex.org/W2735494839","https://openalex.org/W2790108014","https://openalex.org/W2962858109","https://openalex.org/W2962945654","https://openalex.org/W2963211188","https://openalex.org/W2970281653","https://openalex.org/W3004531689","https://openalex.org/W3006110666","https://openalex.org/W3008985036","https://openalex.org/W3010659930","https://openalex.org/W3011149445","https://openalex.org/W3014337038","https://openalex.org/W3014581483","https://openalex.org/W3014666486","https://openalex.org/W3014993555","https://openalex.org/W3017016822","https://openalex.org/W3019531985","https://openalex.org/W3021622280","https://openalex.org/W3024506939","https://openalex.org/W3025800305","https://openalex.org/W3026717770","https://openalex.org/W3048828727","https://openalex.org/W3049757379","https://openalex.org/W3083753334","https://openalex.org/W3085306326","https://openalex.org/W3090325688","https://openalex.org/W3099805905","https://openalex.org/W3100818123","https://openalex.org/W3102469298","https://openalex.org/W3105081694","https://openalex.org/W3116116041","https://openalex.org/W3125771089","https://openalex.org/W3135715469","https://openalex.org/W3137180645","https://openalex.org/W3197583914","https://openalex.org/W3201420012","https://openalex.org/W3202232851","https://openalex.org/W3208239477","https://openalex.org/W3209574471","https://openalex.org/W4200161740","https://openalex.org/W4220728591","https://openalex.org/W4253368012","https://openalex.org/W4280546964","https://openalex.org/W4294740541","https://openalex.org/W4302028121","https://openalex.org/W6679852000","https://openalex.org/W6738045163","https://openalex.org/W7015098694","https://openalex.org/W7042912420"],"related_works":["https://openalex.org/W4382894326","https://openalex.org/W3035105474","https://openalex.org/W4205698903","https://openalex.org/W4294968941","https://openalex.org/W4205413867","https://openalex.org/W3179695362","https://openalex.org/W3175450294","https://openalex.org/W3135208316","https://openalex.org/W4375867731","https://openalex.org/W4380075502"],"abstract_inverted_index":{"Coronavirus":[0],"disease":[1],"2019":[2],"(COVID-19)":[3],"generated":[4],"a":[5,28,79,107],"global":[6],"public":[7],"health":[8],"emergency":[9],"since":[10],"December":[11],"2019,":[12],"causing":[13],"huge":[14],"economic":[15],"losses.":[16],"To":[17],"help":[18,173],"radiologists":[19],"strengthen":[20],"their":[21],"recognition":[22],"of":[23,58,71,97,186],"COVID-19":[24,162],"cases,":[25],"we":[26,105],"developed":[27],"computer-aided":[29],"diagnosis":[30,185],"system":[31,155],"based":[32],"on":[33,133],"deep":[34],"learning":[35,81,96],"to":[36,62,172,182],"automatically":[37],"classify":[38],"chest":[39],"computed":[40],"tomography-based":[41],"COVID-19,":[42],"Tuberculosis,":[43],"and":[44,93,121,143,178,181,189],"healthy":[45],"control":[46],"subjects.":[47],"Our":[48,153],"novel":[49,108,154],"classification":[50,146],"model":[51,84,111],"AdaD-FNN":[52],"sequentially":[53],"transfers":[54],"the":[55,63,69,72,75,86,90,95,101,115,123,144,184,197],"trained":[56],"knowledge":[57],"an":[59],"FNN":[60,65],"estimator":[61,66],"next":[64],"while":[67],"updating":[68],"weights":[70],"samples":[73],"in":[74,100,196],"training":[76],"set":[77],"with":[78,166],"decaying":[80],"rate.":[82],"This":[83],"inhibits":[85],"network":[87],"from":[88],"remembering":[89],"noisy":[91],"information":[92],"improves":[94],"complex":[98],"patterns":[99],"hard-to-identify":[102],"samples.":[103],"Moreover,":[104],"designed":[106],"image":[109,116],"preprocessing":[110],"F-U2MNet-C":[112],"by":[113],"enhancing":[114],"features":[117],"using":[118,126],"fuzzy":[119],"stacking":[120],"eliminating":[122],"interference":[124],"factors":[125],"U2MNet":[127],"segmentation.":[128],"Extensive":[129],"experiments":[130],"are":[131,148],"conducted":[132],"four":[134],"publicly":[135],"available":[136],"datasets":[137],"namely,":[138],"TLDCA,":[139],"UCSD-Al4H,":[140],"SARS-CoV-2,":[141],"TCIA,":[142],"obtained":[145],"accuracies":[147],"99.52%,":[149],"92.96%,":[150],"97.86%,":[151],"91.97%.":[152],"gives":[156],"out":[157],"compelling":[158],"performance":[159],"for":[160],"assisting":[161],"detection":[163],"when":[164],"compared":[165],"22":[167],"state-of-the-art":[168],"methods.":[169],"We":[170],"hope":[171],"link":[174],"together":[175],"biomedical":[176],"research":[177],"artificial":[179],"intelligence":[180],"assist":[183],"doctors,":[187],"radiologists,":[188],"inspectors":[190],"at":[191],"each":[192],"epidemic":[193],"prevention":[194],"site":[195],"real":[198],"world.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
