{"id":"https://openalex.org/W4213117425","doi":"https://doi.org/10.1109/jbhi.2022.3151171","title":"COVID Detection From Chest X-Ray Images Using Multi-Scale Attention","display_name":"COVID Detection From Chest X-Ray Images Using Multi-Scale Attention","publication_year":2022,"publication_date":"2022-02-14","ids":{"openalex":"https://openalex.org/W4213117425","doi":"https://doi.org/10.1109/jbhi.2022.3151171","pmid":"https://pubmed.ncbi.nlm.nih.gov/35157603"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2022.3151171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2022.3151171","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":null,"license_id":null,"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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075943854","display_name":"Abhinav Dhere","orcid":"https://orcid.org/0000-0003-2089-1085"},"institutions":[{"id":"https://openalex.org/I64189192","display_name":"International Institute of Information Technology, Hyderabad","ror":"https://ror.org/05f11g639","country_code":"IN","type":"education","lineage":["https://openalex.org/I64189192"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Abhinav Dhere","raw_affiliation_strings":["Center for Visual Information Technology, International Institute of Information Technology, Hyderabad, Telangana, India"],"raw_orcid":"https://orcid.org/0000-0003-2089-1085","affiliations":[{"raw_affiliation_string":"Center for Visual Information Technology, International Institute of Information Technology, Hyderabad, Telangana, India","institution_ids":["https://openalex.org/I64189192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026537714","display_name":"Jayanthi Sivaswamy","orcid":"https://orcid.org/0000-0002-2474-9898"},"institutions":[{"id":"https://openalex.org/I64189192","display_name":"International Institute of Information Technology, Hyderabad","ror":"https://ror.org/05f11g639","country_code":"IN","type":"education","lineage":["https://openalex.org/I64189192"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jayanthi Sivaswamy","raw_affiliation_strings":["Center for Visual Information Technology, International Institute of Information Technology, Hyderabad, Telangana, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Visual Information Technology, International Institute of Information Technology, Hyderabad, Telangana, India","institution_ids":["https://openalex.org/I64189192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.3855,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.92615658,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"26","issue":"4","first_page":"1496","last_page":"1505"},"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":0.9897000193595886,"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9745000004768372,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.7161416411399841},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6764278411865234},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6528645753860474},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5758370161056519},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5055923461914062},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.45228099822998047},{"id":"https://openalex.org/keywords/pneumonia","display_name":"Pneumonia","score":0.445367693901062},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.21546036005020142},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.16260948777198792},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.1609201431274414},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15494927763938904}],"concepts":[{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.7161416411399841},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6764278411865234},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6528645753860474},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5758370161056519},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5055923461914062},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.45228099822998047},{"id":"https://openalex.org/C2777914695","wikidata":"https://www.wikidata.org/wiki/Q12192","display_name":"Pneumonia","level":2,"score":0.445367693901062},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.21546036005020142},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.16260948777198792},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.1609201431274414},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15494927763938904},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"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":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","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":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","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":"D011014","descriptor_name":"Pneumonia","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011014","descriptor_name":"Pneumonia","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011014","descriptor_name":"Pneumonia","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"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},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/jbhi.2022.3151171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2022.3151171","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},{"id":"pmid:35157603","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35157603","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":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2438189022","https://openalex.org/W2570343428","https://openalex.org/W2752782242","https://openalex.org/W2788633781","https://openalex.org/W2914959431","https://openalex.org/W2962858109","https://openalex.org/W2962914239","https://openalex.org/W2963351448","https://openalex.org/W2963446712","https://openalex.org/W2963466845","https://openalex.org/W2963495494","https://openalex.org/W3006110666","https://openalex.org/W3007497549","https://openalex.org/W3010381061","https://openalex.org/W3014782447","https://openalex.org/W3017855299","https://openalex.org/W3023402713","https://openalex.org/W3028070348","https://openalex.org/W3033814865","https://openalex.org/W3035281110","https://openalex.org/W3042504804","https://openalex.org/W3046166186","https://openalex.org/W3049757379","https://openalex.org/W3080568059","https://openalex.org/W3083753334","https://openalex.org/W3085708132","https://openalex.org/W3101633406","https://openalex.org/W3105081694","https://openalex.org/W3134583934","https://openalex.org/W3142371777","https://openalex.org/W3173455503","https://openalex.org/W4251216503","https://openalex.org/W4394654459"],"related_works":["https://openalex.org/W4382894326","https://openalex.org/W3035105474","https://openalex.org/W4205698903","https://openalex.org/W2560215812","https://openalex.org/W4294968941","https://openalex.org/W4390279739","https://openalex.org/W2949601986","https://openalex.org/W4205413867","https://openalex.org/W3179695362","https://openalex.org/W3087333412"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"based":[2,81],"methods":[3],"have":[4],"shown":[5],"great":[6],"promise":[7],"in":[8,26,165,199,213,224],"achieving":[9],"accurate":[10],"automatic":[11],"detection":[12],"of":[13,168,192,202,232],"Coronavirus":[14],"Disease":[15],"(covid)":[16],"-":[17],"19":[18],"from":[19,103,109],"Chest":[20],"X-Ray":[21],"(cxr)":[22],"images.However,":[23],"incorporating":[24],"explainability":[25],"these":[27],"solutions":[28],"remains":[29],"relatively":[30],"less":[31],"explored.":[32],"We":[33,51,61,161],"present":[34],"a":[35,65,77,100,128],"hierarchical":[36],"classification":[37,91],"approach":[38],"for":[39,84,147],"separating":[40],"normal,":[41],"non-covid":[42],"pneumonia":[43,107],"(ncp)":[44],"and":[45,76,124,138],"covid":[46,123,152,203],"cases":[47,108,111,204],"using":[48,64],"cxr":[49],"images.":[50],"demonstrate":[52],"that":[53,186],"the":[54,86,113,117,132,158,166,189,193,200,219,230,233],"proposed":[55,87,90,133],"method":[56,134],"achieves":[57,135],"clinically":[58],"consistent":[59],"explainations.":[60],"achieve":[62],"this":[63],"novel":[66],"multi-scale":[67],"attention":[68],"architecture":[69,119],"called":[70],"Multi-scale":[71],"Attention":[72],"Residual":[73],"Learning":[74],"(marl)":[75],"new":[78],"loss":[79],"function":[80],"on":[82],"conicity":[83],"training":[85],"architecture.":[88],"The":[89,96,178],"strategy":[92],"has":[93],"two":[94],"stages.":[95],"first":[97],"stage":[98,115],"uses":[99,116],"model":[101],"derived":[102,234],"DenseNet":[104],"to":[105,120,157,183,195,229],"separate":[106],"normal":[110,148],"while":[112,205],"second":[114],"marl":[118,187],"discriminate":[121],"between":[122],"ncp":[125,150,214],"cases.":[126,215],"With":[127],"five-fold":[129],"cross":[130],"validation":[131],"93%,":[136],"96.28%,":[137],"84.51%":[139],"accuracy":[140],"respectively":[141],"over":[142],"three":[143],"large,":[144],"public":[145],"datasets":[146],"vs.":[149,151],"classification.":[153],"This":[154,216],"is":[155],"competitive":[156],"state-of-the-art":[159],"methods.":[160],"also":[162,181],"provide":[163],"explanations":[164],"form":[167],"GradCAM":[169],"attributions,":[170],"which":[171],"are":[172,180,208],"well":[173],"aligned":[174],"with":[175],"expert":[176],"annotations.":[177],"attributions":[179],"seen":[182,209],"clearly":[184],"indicate":[185],"deems":[188],"peripheral":[190],"regions":[191,207],"lungs":[194],"be":[196],"more":[197,211],"important":[198,212],"case":[201],"central":[206],"as":[210],"observation":[217],"matches":[218],"criteria":[220],"described":[221],"by":[222],"radiologists":[223],"clinical":[225],"literature,":[226],"thereby":[227],"attesting":[228],"utility":[231],"explanations.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":5}],"updated_date":"2026-06-20T22:02:38.213706","created_date":"2025-10-10T00:00:00"}
