{"id":"https://openalex.org/W4409848827","doi":"https://doi.org/10.32604/cmc.2025.063257","title":"A Pneumonia Recognition Model Based on Multiscale Attention Improved EfficientNetV2","display_name":"A Pneumonia Recognition Model Based on Multiscale Attention Improved EfficientNetV2","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409848827","doi":"https://doi.org/10.32604/cmc.2025.063257"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.063257","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.063257","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.063257","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101968159","display_name":"Zhigao Zeng","orcid":"https://orcid.org/0000-0001-5780-2571"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhigao Zeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361979","display_name":"Jun Liu","orcid":"https://orcid.org/0000-0002-9001-9498"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Liu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101974805","display_name":"Bing Zheng","orcid":"https://orcid.org/0000-0003-2295-3569"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bing Zheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004706129","display_name":"Shengqiu Yi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shengqiu Yi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089592676","display_name":"Xinpan Yuan","orcid":"https://orcid.org/0000-0001-9509-0755"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xinpan Yuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5028851907","display_name":"Qiang Liu","orcid":"https://orcid.org/0000-0002-7707-1099"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiang Liu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101968159"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15228465,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"84","issue":"1","first_page":"513","last_page":"536"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.7621999979019165,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"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/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.7621999979019165,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative 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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.7617999911308289,"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/T13161","display_name":"Ideological and Political Education","score":0.742900013923645,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pneumonia","display_name":"Pneumonia","score":0.5876024961471558},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45804494619369507},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.39486366510391235},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3344913721084595},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.12122946977615356}],"concepts":[{"id":"https://openalex.org/C2777914695","wikidata":"https://www.wikidata.org/wiki/Q12192","display_name":"Pneumonia","level":2,"score":0.5876024961471558},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45804494619369507},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.39486366510391235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3344913721084595},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.12122946977615356}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.063257","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.063257","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.063257","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.063257","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2051838543","https://openalex.org/W2110290656","https://openalex.org/W2139878679","https://openalex.org/W2788633781","https://openalex.org/W2924911266","https://openalex.org/W2963351448","https://openalex.org/W3012774668","https://openalex.org/W3033616466","https://openalex.org/W3126395150","https://openalex.org/W4200130386","https://openalex.org/W4200363845","https://openalex.org/W4280493037","https://openalex.org/W4306839706","https://openalex.org/W4309196090","https://openalex.org/W4379207370","https://openalex.org/W4393308750","https://openalex.org/W4398141531","https://openalex.org/W4402203360","https://openalex.org/W4411939329"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W3031052312","https://openalex.org/W4389568370","https://openalex.org/W3032375762","https://openalex.org/W1995515455","https://openalex.org/W2080531066","https://openalex.org/W3108674512","https://openalex.org/W1506200166"],"abstract_inverted_index":{"To":[0],"solve":[1],"the":[2,17,37,44,52,58,64,68,89,103,110,127,143,160,164,179,184,196,232,238,256,260,266,276],"problems":[3],"of":[4,39,43,67,105,150,166,176,183,192,202,231,263],"complex":[5,135],"lesion":[6,136],"region":[7],"morphology,":[8],"blurred":[9],"edges,":[10],"and":[11,95,163,172,205,215,218,222,282],"limited":[12],"hardware":[13],"resources":[14],"for":[15,131,245,285],"deploying":[16],"recognition":[18,28,112,129,200,280],"model":[19,29,45,106,145,167,223,240,258,277],"in":[20,57,82,247],"pneumonia":[21,27,132,286],"image":[22,287],"recognition,":[23],"an":[24,115,174,190],"improved":[25,73,116,144,257],"EfficientNetV2":[26],"based":[30],"on":[31,178,209,265],"multiscale":[32],"attention":[33,91,120],"is":[34,46,55,80,85,99,123,154,169],"proposed.":[35],"First,":[36],"number":[38,104,165],"main":[40],"module":[41,79,98,122],"stacks":[42],"reduced":[47,155],"to":[48,62,87,92,101,125,159,195,271],"avoid":[49],"overfitting,":[50],"while":[51,108],"dilated":[53],"convolution":[54,77],"introduced":[56,86,100],"first":[59],"convolutional":[60],"layer":[61],"expand":[63],"receptive":[65],"field":[66],"model;":[69],"second,":[70],"a":[71,96,147],"redesigned":[72],"mobile":[74,251],"inverted":[75],"bottleneck":[76],"(IMBConv)":[78],"proposed,":[81],"which":[83,153],"GSConv":[84],"enhance":[88],"model\u2019s":[90,111,128],"inter-channel":[93],"information,":[94],"SimAM":[97],"reduce":[102],"parameters":[107,168],"guaranteeing":[109],"performance;":[113],"finally,":[114],"multi-scale":[117],"efficient":[118],"local":[119],"(MELA)":[121],"proposed":[124,233,239],"ensure":[126],"ability":[130,284],"images":[133],"with":[134],"regions.":[137],"The":[138,199],"experimental":[139],"results":[140],"show":[141],"that":[142,237,275],"has":[146,241,278],"computational":[148,220],"complexity":[149],"1.96":[151],"GFLOPs,":[152],"by":[156],"32%":[157],"relative":[158],"baseline":[161,197],"model,":[162],"also":[170],"reduced,":[171],"achieves":[173],"accuracy":[175,262,281],"86.67%":[177],"triple":[180],"classification":[181],"task":[182],"public":[185,268],"dataset":[186,211,269],"Chest":[187],"X-ray,":[188],"representing":[189],"improvement":[191],"2.74%":[193],"compared":[194,270],"model.":[198,234],"accuracies":[201],"ResNet50,":[203],"Inception-V4,":[204],"Swin":[206],"Transformer":[207],"V2":[208],"this":[210],"are":[212,226],"84.36%,":[213],"85.98%,":[214],"83.42%,":[216],"respectively,":[217],"their":[219],"complexities":[221],"parameter":[224],"counts":[225],"all":[227],"higher":[228],"than":[229],"those":[230],"This":[235],"indicates":[236],"very":[242],"high":[243],"feasibility":[244],"deployment":[246],"edge":[248],"computing":[249],"or":[250],"healthcare":[252],"systems.":[253],"In":[254],"addition,":[255],"achieved":[259],"highest":[261],"90.98%":[264],"four-classification":[267],"other":[272],"models,":[273],"indicating":[274],"better":[279],"generalization":[283],"recognition.":[288]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}