{"id":"https://openalex.org/W4306835744","doi":"https://doi.org/10.3390/s22207977","title":"Classification and Detection of COVID-19 and Other Chest-Related Diseases Using Transfer Learning","display_name":"Classification and Detection of COVID-19 and Other Chest-Related Diseases Using Transfer Learning","publication_year":2022,"publication_date":"2022-10-19","ids":{"openalex":"https://openalex.org/W4306835744","doi":"https://doi.org/10.3390/s22207977","pmid":"https://pubmed.ncbi.nlm.nih.gov/36298328"},"language":"en","primary_location":{"id":"doi:10.3390/s22207977","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22207977","pdf_url":"https://www.mdpi.com/1424-8220/22/20/7977/pdf?version=1666178732","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"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":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/20/7977/pdf?version=1666178732","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003308322","display_name":"Muhammad Tahir Naseem","orcid":"https://orcid.org/0000-0001-6659-097X"},"institutions":[{"id":"https://openalex.org/I195024194","display_name":"Riphah International University","ror":"https://ror.org/02kdm5630","country_code":"PK","type":"education","lineage":["https://openalex.org/I195024194"]},{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR","PK"],"is_corresponding":false,"raw_author_name":"Muhammad Tahir Naseem","raw_affiliation_strings":["Department of Electronic Engineering, Yeungnam University, Gyeongsan 38541, Korea","Riphah School of Computing & Applied Sciences (RSCI), Riphah International University, Lahore 55150, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Yeungnam University, Gyeongsan 38541, Korea","institution_ids":["https://openalex.org/I55240360"]},{"raw_affiliation_string":"Riphah School of Computing & Applied Sciences (RSCI), Riphah International University, Lahore 55150, Pakistan","institution_ids":["https://openalex.org/I195024194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082574284","display_name":"Tajmal Hussain","orcid":null},"institutions":[{"id":"https://openalex.org/I195024194","display_name":"Riphah International University","ror":"https://ror.org/02kdm5630","country_code":"PK","type":"education","lineage":["https://openalex.org/I195024194"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Tajmal Hussain","raw_affiliation_strings":["Riphah School of Computing & Applied Sciences (RSCI), Riphah International University, Lahore 55150, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Riphah School of Computing & Applied Sciences (RSCI), Riphah International University, Lahore 55150, Pakistan","institution_ids":["https://openalex.org/I195024194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069768212","display_name":"Chan-Su Lee","orcid":"https://orcid.org/0000-0001-9606-0646"},"institutions":[{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Chan-Su Lee","raw_affiliation_strings":["Department of Electronic Engineering, Yeungnam University, Gyeongsan 38541, Korea"],"raw_orcid":"https://orcid.org/0000-0001-9606-0646","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Yeungnam University, Gyeongsan 38541, Korea","institution_ids":["https://openalex.org/I55240360"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009282836","display_name":"Muhammad Adnan Khan","orcid":"https://orcid.org/0000-0003-4854-9935"},"institutions":[{"id":"https://openalex.org/I195024194","display_name":"Riphah International University","ror":"https://ror.org/02kdm5630","country_code":"PK","type":"education","lineage":["https://openalex.org/I195024194"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Muhammad Adnan Khan","raw_affiliation_strings":["Riphah School of Computing & Applied Sciences (RSCI), Riphah International University, Lahore 55150, Pakistan"],"raw_orcid":"https://orcid.org/0000-0003-4854-9935","affiliations":[{"raw_affiliation_string":"Riphah School of Computing & Applied Sciences (RSCI), Riphah International University, Lahore 55150, Pakistan","institution_ids":["https://openalex.org/I195024194"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5069768212"],"corresponding_institution_ids":["https://openalex.org/I55240360"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":1.0409,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.74695667,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"22","issue":"20","first_page":"7977","last_page":"7977"},"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/T10862","display_name":"AI in cancer detection","score":0.972100019454956,"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"}},{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9639000296592712,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7182695269584656},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.6563180685043335},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6488515138626099},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.58937668800354},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5773329138755798},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5261715650558472},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5238859057426453},{"id":"https://openalex.org/keywords/pneumonia","display_name":"Pneumonia","score":0.5039276480674744},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47647568583488464},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4209938049316406},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.33917689323425293},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.1988171935081482},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.09996941685676575}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7182695269584656},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.6563180685043335},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6488515138626099},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.58937668800354},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5773329138755798},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5261715650558472},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5238859057426453},{"id":"https://openalex.org/C2777914695","wikidata":"https://www.wikidata.org/wiki/Q12192","display_name":"Pneumonia","level":2,"score":0.5039276480674744},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47647568583488464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4209938049316406},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.33917689323425293},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.1988171935081482},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.09996941685676575},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"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":[{"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":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000175","qualifier_name":"diagnosis","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":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","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":"D011024","descriptor_name":"Pneumonia, Viral","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011024","descriptor_name":"Pneumonia, Viral","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011024","descriptor_name":"Pneumonia, Viral","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011030","descriptor_name":"Pneumothorax","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011030","descriptor_name":"Pneumothorax","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011030","descriptor_name":"Pneumothorax","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D018410","descriptor_name":"Pneumonia, Bacterial","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D018410","descriptor_name":"Pneumonia, Bacterial","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D018410","descriptor_name":"Pneumonia, Bacterial","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22207977","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22207977","pdf_url":"https://www.mdpi.com/1424-8220/22/20/7977/pdf?version=1666178732","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"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":"Sensors","raw_type":"journal-article"},{"id":"pmid:36298328","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36298328","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":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:9610066","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9610066","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:08ff41c8ffa7468880f31148590c1aed","is_oa":true,"landing_page_url":"https://doaj.org/article/08ff41c8ffa7468880f31148590c1aed","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":"Sensors, Vol 22, Iss 20, p 7977 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/20/7977/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22207977","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":"Sensors; Volume 22; Issue 20; Pages: 7977","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22207977","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22207977","pdf_url":"https://www.mdpi.com/1424-8220/22/20/7977/pdf?version=1666178732","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"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":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.44999998807907104}],"awards":[{"id":"https://openalex.org/G6765871644","display_name":null,"funder_award_id":"2021R1A1A03040177","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4306835744.pdf","grobid_xml":"https://content.openalex.org/works/W4306835744.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W592081968","https://openalex.org/W1994062553","https://openalex.org/W2010382953","https://openalex.org/W2061715187","https://openalex.org/W2117539524","https://openalex.org/W2118978333","https://openalex.org/W2309023520","https://openalex.org/W2618530766","https://openalex.org/W2777186991","https://openalex.org/W2788633781","https://openalex.org/W2795964626","https://openalex.org/W2913363989","https://openalex.org/W2936503027","https://openalex.org/W2942329488","https://openalex.org/W2954074628","https://openalex.org/W3008874180","https://openalex.org/W3010702679","https://openalex.org/W3013277995","https://openalex.org/W3013507463","https://openalex.org/W3013601031","https://openalex.org/W3016488464","https://openalex.org/W3017644243","https://openalex.org/W3017855299","https://openalex.org/W3020923611","https://openalex.org/W3027682070","https://openalex.org/W3030621456","https://openalex.org/W3032017599","https://openalex.org/W3033616466","https://openalex.org/W3039563973","https://openalex.org/W3043091553","https://openalex.org/W3089168916","https://openalex.org/W3105081694","https://openalex.org/W3111042139","https://openalex.org/W3132499588","https://openalex.org/W3138438229","https://openalex.org/W3154603462","https://openalex.org/W3162351260","https://openalex.org/W3167147947","https://openalex.org/W3173728300","https://openalex.org/W4205752017","https://openalex.org/W6774964072","https://openalex.org/W6780728126","https://openalex.org/W6787245061","https://openalex.org/W7053126446"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2397288865","https://openalex.org/W3183901164","https://openalex.org/W2951211570","https://openalex.org/W3176438653","https://openalex.org/W3135818718","https://openalex.org/W4290188444","https://openalex.org/W3003905048","https://openalex.org/W2253429366","https://openalex.org/W3127975138"],"abstract_inverted_index":{"COVID-19":[0,17,76],"has":[1],"infected":[2],"millions":[3],"of":[4,75,86,120,132,227],"people":[5],"worldwide":[6],"over":[7],"the":[8,72,144],"past":[9],"few":[10],"years.":[11],"The":[12,162],"main":[13],"technique":[14,70],"used":[15,155],"for":[16,71,127,137],"detection":[18,44,74],"is":[19,23,32],"reverse":[20],"transcription,":[21],"which":[22],"expensive,":[24],"sensitive,":[25],"and":[26,35,77,102,111,142,174,180,189,199,201,211,218,232],"requires":[27],"medical":[28],"expertise.":[29],"X-ray":[30,84,123],"imaging":[31,60],"an":[33],"alternative":[34],"more":[36],"accessible":[37],"technique.":[38],"This":[39,66],"study":[40,67],"aimed":[41],"to":[42,46,166],"improve":[43],"accuracy":[45,226],"create":[47],"a":[48,69,159,224],"computer-aided":[49],"diagnostic":[50],"tool.":[51],"Combining":[52],"other":[53,78],"artificial":[54],"intelligence":[55],"applications":[56],"techniques":[57],"with":[58,125,135,147,156],"radiological":[59],"can":[61],"help":[62],"detect":[63],"different":[64],"diseases.":[65],"proposes":[68],"automatic":[73],"chest-related":[79],"diseases":[80],"using":[81,168],"digital":[82],"chest":[83,122],"images":[85,113,124,134],"suspected":[87],"patients":[88],"by":[89,106],"applying":[90],"transfer":[91],"learning":[92],"(TL)":[93],"algorithms.":[94],"For":[95,213],"this":[96],"purpose,":[97],"two":[98],"balanced":[99],"datasets,":[100],"Dataset-1":[101,118],"Dataset-2,":[103],"were":[104],"created":[105],"combining":[107],"four":[108],"public":[109],"databases":[110],"collecting":[112],"from":[114],"recently":[115],"published":[116],"articles.":[117],"consisted":[119,131],"6000":[121],"1500":[126],"each":[128,138],"class.":[129,139],"Dataset-2":[130],"7200":[133],"1200":[136],"To":[140],"train":[141],"test":[143],"model,":[145],"TL":[146],"nine":[148],"pretrained":[149],"convolutional":[150],"neural":[151],"networks":[152],"(CNNs)":[153],"was":[154,164],"augmentation":[157],"as":[158],"preprocessing":[160],"method.":[161],"network":[163],"trained":[165],"classify":[167],"five":[169],"classifiers:":[170],"two-class":[171],"classifier":[172,177,184,193,203],"(normal":[173],"COVID-19);":[175],"three-class":[176],"(normal,":[178,185,194,204],"COVID-19,":[179,188,197,207],"viral":[181,186,208],"pneumonia),":[182],"four-class":[183],"pneumonia,":[187,196,206,209],"tuberculosis":[190],"(Tb)),":[191],"five-class":[192],"bacterial":[195,205],"Tb,":[198,210],"pneumothorax),":[200],"six-class":[202],"pneumothorax).":[212],"two,":[214],"three,":[215],"four,":[216],"five,":[217],"six":[219],"classes,":[220],"our":[221],"model":[222],"achieved":[223],"maximum":[225],"99.83,":[228],"98.11,":[229],"97.00,":[230],"94.66,":[231],"87.29%,":[233],"respectively.":[234]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}
