{"id":"https://openalex.org/W3120374612","doi":"https://doi.org/10.3390/sym13010113","title":"An Ensemble of Global and Local-Attention Based Convolutional Neural Networks for COVID-19 Diagnosis on Chest X-ray Images","display_name":"An Ensemble of Global and Local-Attention Based Convolutional Neural Networks for COVID-19 Diagnosis on Chest X-ray Images","publication_year":2021,"publication_date":"2021-01-11","ids":{"openalex":"https://openalex.org/W3120374612","doi":"https://doi.org/10.3390/sym13010113","mag":"3120374612"},"language":"en","primary_location":{"id":"doi:10.3390/sym13010113","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13010113","pdf_url":"https://www.mdpi.com/2073-8994/13/1/113/pdf?version=1610365395","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/13/1/113/pdf?version=1610365395","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062965682","display_name":"Ahmed Afifi","orcid":"https://orcid.org/0000-0002-8434-8578"},"institutions":[{"id":"https://openalex.org/I4626487","display_name":"King Faisal University","ror":"https://ror.org/00dn43547","country_code":"SA","type":"education","lineage":["https://openalex.org/I4626487"]},{"id":"https://openalex.org/I63601056","display_name":"Menoufia University","ror":"https://ror.org/05sjrb944","country_code":"EG","type":"education","lineage":["https://openalex.org/I63601056"]}],"countries":["EG","SA"],"is_corresponding":true,"raw_author_name":"Ahmed Afifi","raw_affiliation_strings":["Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia","Faculty of Computers and Information, Menoufia University, Menoufia 32511, Egypt"],"raw_orcid":"https://orcid.org/0000-0002-8434-8578","affiliations":[{"raw_affiliation_string":"Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia","institution_ids":["https://openalex.org/I4626487"]},{"raw_affiliation_string":"Faculty of Computers and Information, Menoufia University, Menoufia 32511, Egypt","institution_ids":["https://openalex.org/I63601056"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077540771","display_name":"Noor E. Hafsa","orcid":"https://orcid.org/0000-0002-8288-1782"},"institutions":[{"id":"https://openalex.org/I4626487","display_name":"King Faisal University","ror":"https://ror.org/00dn43547","country_code":"SA","type":"education","lineage":["https://openalex.org/I4626487"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Noor E Hafsa","raw_affiliation_strings":["Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-8288-1782","affiliations":[{"raw_affiliation_string":"Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia","institution_ids":["https://openalex.org/I4626487"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044856698","display_name":"Mona A. S. Ali","orcid":"https://orcid.org/0000-0002-2192-3504"},"institutions":[{"id":"https://openalex.org/I4626487","display_name":"King Faisal University","ror":"https://ror.org/00dn43547","country_code":"SA","type":"education","lineage":["https://openalex.org/I4626487"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mona A. S. Ali","raw_affiliation_strings":["Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-2192-3504","affiliations":[{"raw_affiliation_string":"Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia","institution_ids":["https://openalex.org/I4626487"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042394003","display_name":"Abdulaziz Alhumam","orcid":"https://orcid.org/0000-0001-7778-2838"},"institutions":[{"id":"https://openalex.org/I4626487","display_name":"King Faisal University","ror":"https://ror.org/00dn43547","country_code":"SA","type":"education","lineage":["https://openalex.org/I4626487"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Abdulaziz Alhumam","raw_affiliation_strings":["Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia","institution_ids":["https://openalex.org/I4626487"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029934064","display_name":"Safa Alsalman","orcid":null},"institutions":[{"id":"https://openalex.org/I4626487","display_name":"King Faisal University","ror":"https://ror.org/00dn43547","country_code":"SA","type":"education","lineage":["https://openalex.org/I4626487"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Safa Alsalman","raw_affiliation_strings":["Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia","institution_ids":["https://openalex.org/I4626487"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5062965682"],"corresponding_institution_ids":["https://openalex.org/I4626487","https://openalex.org/I63601056"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":5.8804,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.96734395,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"13","issue":"1","first_page":"113","last_page":"113"},"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":0.9775000214576721,"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/T10862","display_name":"AI in cancer detection","score":0.9704999923706055,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7511389851570129},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7401622533798218},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7222994565963745},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6076993346214294},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5291346311569214},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5270025134086609},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4753111004829407},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.4716055989265442},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.46455782651901245},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.43838247656822205}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7511389851570129},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7401622533798218},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7222994565963745},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6076993346214294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5291346311569214},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5270025134086609},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4753111004829407},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.4716055989265442},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.46455782651901245},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.43838247656822205},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym13010113","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13010113","pdf_url":"https://www.mdpi.com/2073-8994/13/1/113/pdf?version=1610365395","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c4190d7270cb444e834e8b3177d7c1c9","is_oa":true,"landing_page_url":"https://doaj.org/article/c4190d7270cb444e834e8b3177d7c1c9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 13, Iss 1, p 113 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/13/1/113/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym13010113","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym13010113","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13010113","pdf_url":"https://www.mdpi.com/2073-8994/13/1/113/pdf?version=1610365395","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8299999833106995}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W3120374612.pdf"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W1565746575","https://openalex.org/W1581231885","https://openalex.org/W1849277567","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2542459869","https://openalex.org/W2549139847","https://openalex.org/W2565639579","https://openalex.org/W2743473392","https://openalex.org/W2785934082","https://openalex.org/W2904183610","https://openalex.org/W2912664121","https://openalex.org/W2962708065","https://openalex.org/W2963351448","https://openalex.org/W2963446712","https://openalex.org/W2963466845","https://openalex.org/W2964350391","https://openalex.org/W2996380984","https://openalex.org/W3002715510","https://openalex.org/W3005272159","https://openalex.org/W3006110666","https://openalex.org/W3006882119","https://openalex.org/W3007497549","https://openalex.org/W3007764760","https://openalex.org/W3008985036","https://openalex.org/W3010472505","https://openalex.org/W3012843799","https://openalex.org/W3013042142","https://openalex.org/W3013277995","https://openalex.org/W3013507463","https://openalex.org/W3014561994","https://openalex.org/W3015292413","https://openalex.org/W3015538848","https://openalex.org/W3015571324","https://openalex.org/W3016448052","https://openalex.org/W3017243633","https://openalex.org/W3017317785","https://openalex.org/W3019531985","https://openalex.org/W3022894865","https://openalex.org/W3023402713","https://openalex.org/W3023624960","https://openalex.org/W3023750470","https://openalex.org/W3023769517","https://openalex.org/W3023960016","https://openalex.org/W3029443186","https://openalex.org/W3031759249","https://openalex.org/W3033616466","https://openalex.org/W3033814865","https://openalex.org/W3034709671","https://openalex.org/W3036688711","https://openalex.org/W3085109610","https://openalex.org/W3085331204","https://openalex.org/W3087000505","https://openalex.org/W3087265446","https://openalex.org/W3100523627","https://openalex.org/W3105081694","https://openalex.org/W3108981504","https://openalex.org/W3118634064","https://openalex.org/W3140022118","https://openalex.org/W3162351260","https://openalex.org/W3187183441","https://openalex.org/W4230649743","https://openalex.org/W6631190155","https://openalex.org/W6747701563","https://openalex.org/W6779652059"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W2794896638","https://openalex.org/W3124943098","https://openalex.org/W2891633941","https://openalex.org/W4308112567","https://openalex.org/W3162132941","https://openalex.org/W3202800081"],"abstract_inverted_index":{"The":[0,121,274,293],"recent":[1],"Coronavirus":[2],"Disease":[3],"2019":[4],"(COVID-19)":[5],"pandemic":[6],"has":[7,60],"put":[8],"a":[9,43,153,158,165,216,264,289],"tremendous":[10],"burden":[11],"on":[12,136,225],"global":[13,138,172,243],"health":[14],"systems.":[15],"Medical":[16],"practitioners":[17],"are":[18,40],"under":[19],"great":[20,62],"pressure":[21],"for":[22,64,192],"reliable":[23],"screening":[24],"of":[25,75,126,129,164,167,179,187,208,230,239,253,257,261],"suspected":[26],"cases":[27],"employing":[28],"adjunct":[29],"diagnostic":[30,45,80],"tools":[31],"to":[32,91,107,116,199,280],"standard":[33],"point-of-care":[34],"testing":[35],"methodology.":[36],"Chest":[37],"X-rays":[38],"(CXRs)":[39],"appearing":[41],"as":[42,223],"prospective":[44],"tool":[46],"with":[47,79,233,242,313,317],"easy-to-acquire,":[48],"low-cost":[49],"and":[50,139,157,173,176,210,244,259,271,328],"less":[51],"cross-contamination":[52],"risk":[53],"features.":[54,120],"Artificial":[55],"intelligence":[56],"(AI)-attributed":[57],"CXR":[58,144,185,310],"evaluation":[59],"shown":[61],"potential":[63],"distinguishing":[65],"COVID-19-induced":[66],"pneumonia":[67,308,316],"from":[68,118,143,183,284],"other":[69,211,221,286],"associated":[70,77],"clinical":[71],"instances.":[72],"However,":[73],"one":[74],"the":[76,89,109,113,148,194,206,298,306,323],"challenges":[78],"imaging-based":[81],"modeling":[82],"is":[83,150],"incorrect":[84,324],"feature":[85,325,332],"attribution,":[86],"which":[87],"leads":[88],"model":[90],"learn":[92,117],"misguiding":[93],"disease":[94],"patterns,":[95],"causing":[96],"wrong":[97],"predictions.":[98],"Here,":[99],"we":[100],"demonstrate":[101],"an":[102,127,177,226,237,249,330],"effective":[103],"deep":[104,300],"learning-based":[105,301],"methodology":[106],"mitigate":[108],"problem,":[110,327],"thereby":[111],"allowing":[112],"classification":[114,207,266],"algorithm":[115,302],"relevant":[119],"proposed":[122,299],"deep-learning":[123],"framework":[124,267],"consists":[125],"ensemble":[128,178,238],"convolutional":[130],"neural":[131],"network":[132],"(CNN)":[133],"models":[134,170,241,287],"focusing":[135],"both":[137,180],"local":[140,159,174,245],"pathological":[141,202],"features":[142,203,247],"lung":[145,201],"images,":[146,311],"while":[147],"latter":[149],"extracted":[151],"using":[152,171],"multi-instance":[154],"learning":[155],"scheme":[156],"attention":[160],"mechanism.":[161],"An":[162],"inspection":[163],"series":[166],"backbone":[168],"CNN":[169],"features,":[175,181],"trained":[182],"high-quality":[184],"images":[186],"1311":[188],"patients,":[189],"further":[190],"augmented":[191],"achieving":[193],"symmetry":[195],"in":[196,263,288,309],"class":[197],"distribution,":[198],"localize":[200],"followed":[204],"by":[205,320],"COVID-19":[209],"related":[212],"pneumonia,":[213,270],"shows":[214],"that":[215,297],"DenseNet161":[217,240,275],"architecture":[218],"outperforms":[219],"all":[220,285],"models,":[222],"evaluated":[224],"independent":[227],"test":[228],"set":[229],"159":[231],"patients":[232],"confirmed":[234],"cases.":[235],"Specifically,":[236],"attention-based":[246],"achieve":[248],"average":[250,255],"balanced":[251],"accuracy":[252],"91.2%,":[254],"precision":[256],"92.4%,":[258],"F1-score":[260],"91.9%":[262],"multi-label":[265],"comprising":[268],"COVID-19,":[269],"control":[272],"classes.":[273],"ensembles":[276],"were":[277],"also":[278],"found":[279],"be":[281],"statistically":[282],"significant":[283],"comprehensive":[290],"statistical":[291],"analysis.":[292],"current":[294],"study":[295],"demonstrated":[296],"can":[303],"accurately":[304],"identify":[305],"COVID-19-related":[307],"along":[312],"differentiating":[314],"non-COVID-19-associated":[315],"high":[318],"specificity,":[319],"effectively":[321],"alleviating":[322],"attribution":[326],"exploiting":[329],"enhanced":[331],"descriptor.":[333]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":10}],"updated_date":"2026-06-12T08:23:45.883708","created_date":"2025-10-10T00:00:00"}