{"id":"https://openalex.org/W4291653288","doi":"https://doi.org/10.1109/access.2022.3198958","title":"Thorax Disease Classification Based on Pyramidal Convolution Shuffle Attention Neural Network","display_name":"Thorax Disease Classification Based on Pyramidal Convolution Shuffle Attention Neural Network","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4291653288","doi":"https://doi.org/10.1109/access.2022.3198958"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3198958","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3198958","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2022.3198958","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056849674","display_name":"Kai Chen","orcid":"https://orcid.org/0000-0002-3255-3406"},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kai Chen","raw_affiliation_strings":["College of Electronic Information, Xijing University, Xian, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic Information, Xijing University, Xian, China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036453295","display_name":"Xuqi Wang","orcid":"https://orcid.org/0000-0001-7375-2535"},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuqi Wang","raw_affiliation_strings":["College of Electronic Information, Xijing University, Xian, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic Information, Xijing University, Xian, China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071771834","display_name":"Shanwen Zhang","orcid":"https://orcid.org/0000-0002-4534-5358"},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanwen Zhang","raw_affiliation_strings":["College of Electronic Information, Xijing University, Xian, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic Information, Xijing University, Xian, China","institution_ids":["https://openalex.org/I4210162994"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5056849674"],"corresponding_institution_ids":["https://openalex.org/I4210162994"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.035,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.94473165,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"10","issue":null,"first_page":"85571","last_page":"85581"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9932000041007996,"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"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9883999824523926,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7038103342056274},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6219643354415894},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6050816178321838},{"id":"https://openalex.org/keywords/abnormality","display_name":"Abnormality","score":0.556509256362915},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5380043983459473},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5267000794410706},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4561729431152344},{"id":"https://openalex.org/keywords/thorax","display_name":"Thorax (insect anatomy)","score":0.4547003507614136},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4210112392902374},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.17274919152259827},{"id":"https://openalex.org/keywords/anatomy","display_name":"Anatomy","score":0.10594311356544495}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7038103342056274},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6219643354415894},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6050816178321838},{"id":"https://openalex.org/C50965678","wikidata":"https://www.wikidata.org/wiki/Q2724302","display_name":"Abnormality","level":2,"score":0.556509256362915},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5380043983459473},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5267000794410706},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4561729431152344},{"id":"https://openalex.org/C97834683","wikidata":"https://www.wikidata.org/wiki/Q942508","display_name":"Thorax (insect anatomy)","level":2,"score":0.4547003507614136},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4210112392902374},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.17274919152259827},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.10594311356544495},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3198958","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3198958","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c144647092f84409bfc428ce6315cefa","is_oa":true,"landing_page_url":"https://doaj.org/article/c144647092f84409bfc428ce6315cefa","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 85571-85581 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3198958","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3198958","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.699999988079071}],"awards":[{"id":"https://openalex.org/G7915789691","display_name":null,"funder_award_id":"62172338","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7946611347","display_name":null,"funder_award_id":"212102210005","funder_id":"https://openalex.org/F4320336593","funder_display_name":"Henan Provincial Science and Technology Research Project"},{"id":"https://openalex.org/G8309744380","display_name":null,"funder_award_id":"XJ21B14","funder_id":"https://openalex.org/F4320329602","funder_display_name":"Xijing University"},{"id":"https://openalex.org/G8711467752","display_name":null,"funder_award_id":"62072378","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329602","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63"},{"id":"https://openalex.org/F4320336593","display_name":"Henan Provincial Science and Technology Research Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W2108598243","https://openalex.org/W2168199261","https://openalex.org/W2194775991","https://openalex.org/W2402907716","https://openalex.org/W2611650229","https://openalex.org/W2791966318","https://openalex.org/W2884149198","https://openalex.org/W2897806204","https://openalex.org/W2940151010","https://openalex.org/W2956897601","https://openalex.org/W2962708065","https://openalex.org/W2962838801","https://openalex.org/W2962975664","https://openalex.org/W2963446712","https://openalex.org/W2988214655","https://openalex.org/W2999872673","https://openalex.org/W3002476946","https://openalex.org/W3013277995","https://openalex.org/W3017855299","https://openalex.org/W3030621456","https://openalex.org/W3033814865","https://openalex.org/W3045460727","https://openalex.org/W3071923140","https://openalex.org/W3092125976","https://openalex.org/W3092743670","https://openalex.org/W3099526918","https://openalex.org/W3101156210","https://openalex.org/W3105081694","https://openalex.org/W3113367126","https://openalex.org/W3123686843","https://openalex.org/W3126389275","https://openalex.org/W3128027863","https://openalex.org/W3135057764","https://openalex.org/W3136200549","https://openalex.org/W3139487216","https://openalex.org/W3162342834","https://openalex.org/W3198163615","https://openalex.org/W3202232851","https://openalex.org/W3202345808","https://openalex.org/W4224266319","https://openalex.org/W4246193833","https://openalex.org/W4300485340","https://openalex.org/W4394654459","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6746693533","https://openalex.org/W6748973254"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2964954556"],"abstract_inverted_index":{"Chest":[0],"X-ray":[1,34,52],"is":[2,47,82,161],"one":[3],"of":[4,39,89],"the":[5,15,36,40,57,79,94,104,108,122,129,137],"most":[6],"common":[7],"radiological":[8],"examinations":[9],"for":[10],"screening":[11],"thoracic":[12,29,45,155],"diseases.":[13],"Despite":[14],"existing":[16],"methods":[17],"based":[18,67],"on":[19,56,68,113,121],"convolution":[20,71,81,148],"neural":[21],"network":[22,65],"that":[23,128,146],"have":[24],"achieved":[25],"remarkable":[26],"progress":[27],"in":[28,43,50,163],"disease":[30,156],"classification":[31,157],"from":[32],"chest":[33,51],"images,":[35],"scale":[37],"variation":[38],"pathological":[41,90,115],"abnormalities":[42],"different":[44],"diseases":[46],"still":[48],"challenging":[49],"image":[53],"classification.":[54],"Based":[55],"above":[58],"problems,":[59],"this":[60],"paper":[61],"proposes":[62],"a":[63,69],"residual":[64],"model":[66,110,131],"pyramidal":[70,147],"module":[72,76],"and":[73,124,149],"shuffle":[74,105,150],"attention":[75,106,151],"(PCSANet).":[77],"Specifically,":[78],"pyramid":[80],"used":[83],"to":[84,111],"extract":[85],"more":[86,114],"discriminative":[87],"features":[88],"abnormality":[91,116],"compared":[92,135],"with":[93,136],"standard":[95],"<inline-formula":[96],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[97,165],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[98],"<tex-math":[99],"notation=\"LaTeX\">$3\\times":[100],"3$":[101],"</tex-math></inline-formula>":[102],"convolution;":[103],"enables":[107],"PCSANet":[109,130],"focus":[112],"features.":[117],"The":[118,141,159],"extensive":[119],"experiment":[120],"ChestX-ray14":[123],"COVIDx":[125],"datasets":[126],"demonstrate":[127],"achieves":[132],"superior":[133],"performance":[134],"other":[138],"state-of-the-art":[139],"methods.":[140],"ablation":[142],"study":[143],"further":[144],"proves":[145],"can":[152],"effectively":[153],"improve":[154],"performance.":[158],"code":[160],"published":[162],"<uri":[164],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/Warrior996/PCSANet</uri>":[166],".":[167]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}