{"id":"https://openalex.org/W4403706685","doi":"https://doi.org/10.1186/s40537-024-01018-0","title":"SoftLungX: leveraging transfer learning with convolutional neural networks for accurate respiratory disease classification in chest X-ray images","display_name":"SoftLungX: leveraging transfer learning with convolutional neural networks for accurate respiratory disease classification in chest X-ray images","publication_year":2024,"publication_date":"2024-10-24","ids":{"openalex":"https://openalex.org/W4403706685","doi":"https://doi.org/10.1186/s40537-024-01018-0"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-024-01018-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-024-01018-0","pdf_url":"https://link.springer.com/content/pdf/10.1186/s40537-024-01018-0.pdf","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1186/s40537-024-01018-0.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008564157","display_name":"Tijana Geroski","orcid":"https://orcid.org/0000-0003-1417-0521"},"institutions":[{"id":"https://openalex.org/I14245010","display_name":"University of Kragujevac","ror":"https://ror.org/04f7vj627","country_code":"RS","type":"education","lineage":["https://openalex.org/I14245010"]}],"countries":["RS"],"is_corresponding":true,"raw_author_name":"Tijana Geroski","raw_affiliation_strings":["Bioengineering Research and Development Center (BioIRC), Prvoslava Stojanovi\u0107a 6, 34000, Kragujevac, Serbia","Faculty of Engineering, University of Kragujevac, Sestre Janji\u0107 6, 34000, Kragujevac, Serbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bioengineering Research and Development Center (BioIRC), Prvoslava Stojanovi\u0107a 6, 34000, Kragujevac, Serbia","institution_ids":["https://openalex.org/I14245010"]},{"raw_affiliation_string":"Faculty of Engineering, University of Kragujevac, Sestre Janji\u0107 6, 34000, Kragujevac, Serbia","institution_ids":["https://openalex.org/I14245010"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092556821","display_name":"Ognjen Pavi\u0107","orcid":"https://orcid.org/0000-0003-2533-1079"},"institutions":[{"id":"https://openalex.org/I14245010","display_name":"University of Kragujevac","ror":"https://ror.org/04f7vj627","country_code":"RS","type":"education","lineage":["https://openalex.org/I14245010"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Ognjen Pavi\u0107","raw_affiliation_strings":["Bioengineering Research and Development Center (BioIRC), Prvoslava Stojanovi\u0107a 6, 34000, Kragujevac, Serbia","Institute for Information Technologies Kragujevac, University of Kragujevac, Liceja Kne\u017eevine Srbije 1A, 34000, Kragujevac, Serbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bioengineering Research and Development Center (BioIRC), Prvoslava Stojanovi\u0107a 6, 34000, Kragujevac, Serbia","institution_ids":["https://openalex.org/I14245010"]},{"raw_affiliation_string":"Institute for Information Technologies Kragujevac, University of Kragujevac, Liceja Kne\u017eevine Srbije 1A, 34000, Kragujevac, Serbia","institution_ids":["https://openalex.org/I14245010"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022942714","display_name":"Lazar Da\u0161i\u0107","orcid":"https://orcid.org/0000-0002-8055-100X"},"institutions":[{"id":"https://openalex.org/I14245010","display_name":"University of Kragujevac","ror":"https://ror.org/04f7vj627","country_code":"RS","type":"education","lineage":["https://openalex.org/I14245010"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Lazar Da\u0161i\u0107","raw_affiliation_strings":["Bioengineering Research and Development Center (BioIRC), Prvoslava Stojanovi\u0107a 6, 34000, Kragujevac, Serbia","Institute for Information Technologies Kragujevac, University of Kragujevac, Liceja Kne\u017eevine Srbije 1A, 34000, Kragujevac, Serbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bioengineering Research and Development Center (BioIRC), Prvoslava Stojanovi\u0107a 6, 34000, Kragujevac, Serbia","institution_ids":["https://openalex.org/I14245010"]},{"raw_affiliation_string":"Institute for Information Technologies Kragujevac, University of Kragujevac, Liceja Kne\u017eevine Srbije 1A, 34000, Kragujevac, Serbia","institution_ids":["https://openalex.org/I14245010"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101703743","display_name":"Dragan Milovanovi\u0107","orcid":"https://orcid.org/0000-0002-7728-0608"},"institutions":[{"id":"https://openalex.org/I14245010","display_name":"University of Kragujevac","ror":"https://ror.org/04f7vj627","country_code":"RS","type":"education","lineage":["https://openalex.org/I14245010"]},{"id":"https://openalex.org/I4210154797","display_name":"Clinical Centre of Kragujevac","ror":"https://ror.org/054nax084","country_code":"RS","type":"healthcare","lineage":["https://openalex.org/I4210154797"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Dragan Milovanovi\u0107","raw_affiliation_strings":["Faculty of Medical Sciences, University of Kragujevac, Svetozara Markovi\u0107a 69, 34000, Kragujevac, Serbia","University Clinical Center Kragujevac, Zmaj Jovina 30, 34000, Kragujevac, Serbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Medical Sciences, University of Kragujevac, Svetozara Markovi\u0107a 69, 34000, Kragujevac, Serbia","institution_ids":["https://openalex.org/I14245010"]},{"raw_affiliation_string":"University Clinical Center Kragujevac, Zmaj Jovina 30, 34000, Kragujevac, Serbia","institution_ids":["https://openalex.org/I4210154797","https://openalex.org/I14245010"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042279259","display_name":"Marina Petrovi\u0107","orcid":"https://orcid.org/0000-0001-7646-5144"},"institutions":[{"id":"https://openalex.org/I14245010","display_name":"University of Kragujevac","ror":"https://ror.org/04f7vj627","country_code":"RS","type":"education","lineage":["https://openalex.org/I14245010"]},{"id":"https://openalex.org/I4210154797","display_name":"Clinical Centre of Kragujevac","ror":"https://ror.org/054nax084","country_code":"RS","type":"healthcare","lineage":["https://openalex.org/I4210154797"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Marina Petrovi\u0107","raw_affiliation_strings":["Faculty of Medical Sciences, University of Kragujevac, Svetozara Markovi\u0107a 69, 34000, Kragujevac, Serbia","University Clinical Center Kragujevac, Zmaj Jovina 30, 34000, Kragujevac, Serbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Medical Sciences, University of Kragujevac, Svetozara Markovi\u0107a 69, 34000, Kragujevac, Serbia","institution_ids":["https://openalex.org/I14245010"]},{"raw_affiliation_string":"University Clinical Center Kragujevac, Zmaj Jovina 30, 34000, Kragujevac, Serbia","institution_ids":["https://openalex.org/I4210154797","https://openalex.org/I14245010"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006131395","display_name":"Nenad Filipovi\u0107","orcid":"https://orcid.org/0000-0001-9964-5615"},"institutions":[{"id":"https://openalex.org/I14245010","display_name":"University of Kragujevac","ror":"https://ror.org/04f7vj627","country_code":"RS","type":"education","lineage":["https://openalex.org/I14245010"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Nenad Filipovi\u0107","raw_affiliation_strings":["Bioengineering Research and Development Center (BioIRC), Prvoslava Stojanovi\u0107a 6, 34000, Kragujevac, Serbia","Faculty of Engineering, University of Kragujevac, Sestre Janji\u0107 6, 34000, Kragujevac, Serbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bioengineering Research and Development Center (BioIRC), Prvoslava Stojanovi\u0107a 6, 34000, Kragujevac, Serbia","institution_ids":["https://openalex.org/I14245010"]},{"raw_affiliation_string":"Faculty of Engineering, University of Kragujevac, Sestre Janji\u0107 6, 34000, Kragujevac, Serbia","institution_ids":["https://openalex.org/I14245010"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5008564157"],"corresponding_institution_ids":["https://openalex.org/I14245010"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":1.1327,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.7979324,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"11","issue":"1","first_page":null,"last_page":null},"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9921000003814697,"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":0.9861000180244446,"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/computer-science","display_name":"Computer science","score":0.7913898229598999},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.7860578894615173},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.743405818939209},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4816659688949585},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4182436466217041},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4168270230293274},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3561689257621765},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33685874938964844}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7913898229598999},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7860578894615173},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.743405818939209},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4816659688949585},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4182436466217041},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4168270230293274},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3561689257621765},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33685874938964844}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-024-01018-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-024-01018-0","pdf_url":"https://link.springer.com/content/pdf/10.1186/s40537-024-01018-0.pdf","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:17140b64cd2d4268ba99685ad9e67c72","is_oa":true,"landing_page_url":"https://doaj.org/article/17140b64cd2d4268ba99685ad9e67c72","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":"Journal of Big Data, Vol 11, Iss 1, Pp 1-19 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-024-01018-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-024-01018-0","pdf_url":"https://link.springer.com/content/pdf/10.1186/s40537-024-01018-0.pdf","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8771468119","display_name":null,"funder_award_id":"101016834","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403706685.pdf","grobid_xml":"https://content.openalex.org/works/W4403706685.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1981276685","https://openalex.org/W2015452969","https://openalex.org/W2097117768","https://openalex.org/W2112796928","https://openalex.org/W2194775991","https://openalex.org/W2787072112","https://openalex.org/W2803094129","https://openalex.org/W2894319790","https://openalex.org/W2901794879","https://openalex.org/W2901954625","https://openalex.org/W2948666538","https://openalex.org/W2963446712","https://openalex.org/W2963942157","https://openalex.org/W2971017576","https://openalex.org/W2977613223","https://openalex.org/W2979001271","https://openalex.org/W2998957378","https://openalex.org/W3032290212","https://openalex.org/W3033438356","https://openalex.org/W3045801508","https://openalex.org/W3101156210","https://openalex.org/W4221100204","https://openalex.org/W4234098531","https://openalex.org/W6927646675"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W3183901164","https://openalex.org/W4206357785","https://openalex.org/W4281381188","https://openalex.org/W2951211570","https://openalex.org/W3192840557","https://openalex.org/W3176438653","https://openalex.org/W3103566983"],"abstract_inverted_index":{"Medical":[0],"imaging":[1],"is":[2,155],"an":[3,232],"indispensable":[4],"and":[5,12,55,72,89,136,141,164,204,229,251,273],"very":[6],"important":[7],"step":[8],"in":[9,170,183,260,287],"the":[10,26,36,100,107,156,184,202,222,258,267,298],"diagnosis":[11,313],"treatment":[13],"of":[14,21,104,109,139,143,172,238,269],"illnesses.":[15],"However,":[16],"due":[17],"to":[18,67,225,247],"large":[19],"amounts":[20],"resources":[22],"necessary":[23,295],"for":[24,216,245,249,253,279,311],"training":[25,28],"model,":[27],"from":[29,50,75,86,95,243],"scratch":[30],"may":[31,293],"not":[32,188],"invariably":[33],"emerge":[34],"as":[35,43,118,132,134,167,169,175,177,201,207,300],"optimal":[37],"recourse.":[38],"Transfer":[39],"learning":[40,66,198],"has":[41,187],"emerged":[42],"a":[44,61,96,280,301,307],"viable":[45],"solution,":[46],"where":[47],"pretrained":[48],"weights":[49,206],"ImageNet":[51],"are":[52,148,181,277],"initially":[53],"utilized":[54],"fine-tuninned":[56],"afterwards.":[57],"This":[58],"paper":[59,158],"presents":[60],"novel":[62],"approach":[63],"employing":[64],"transfer":[65,197],"classify":[68],"both":[69],"respiratory":[70],"diseases":[71],"radiological":[73],"findings":[74,276],"chest":[76,91,316],"X-rays.":[77,317],"The":[78,193,219,240],"dataset":[79],"comprises":[80],"191":[81],"660":[82],"X-ray":[83,92],"images":[84,93,142],"gathered":[85],"public":[87],"databases":[88],"752":[90],"obtained":[94],"retrospective":[97],"study":[98],"at":[99],"University":[101],"Clinical":[102],"Center":[103],"Kragujevac,":[105],"forming":[106],"foundation":[108],"Big":[110],"data":[111],"analysis.":[112],"It":[113],"includes":[114],"various":[115],"conditions":[116],"such":[117],"atelectasis,":[119],"cardiomegaly,":[120],"infiltration,":[121],"pleural":[122],"thickening,":[123],"non-viral":[124],"pneumonia,":[125,129],"pneumothorax,":[126],"COVID-19":[127],"viral":[128],"tuberculosis,":[130],"etc.":[131],"well":[133,168],"masses":[135],"nodules":[137,246],"indicative":[138],"tumors":[140],"healthy":[144,163,228],"subjects.":[145],"Although":[146],"there":[147],"existing":[149],"solutions":[150],"with":[151,199,231,266],"some":[152],"diseases,":[153],"this":[154],"first":[157],"that":[159],"inlcludes":[160],"differentiation":[161],"between":[162,227],"diseased":[165],"cases,":[166],"case":[171],"present":[173],"disease,":[174],"much":[176],"18":[178,264],"different":[179],"classes":[180,270],"inlcuded":[182],"analysis,":[185],"which":[186,211],"been":[189],"done":[190],"so":[191],"far.":[192],"proposed":[194],"methodology":[195],"included":[196],"DenseNet121":[200],"backbone":[203],"CheXNeXt":[205],"initialisation":[208],"scheme,":[209],"upon":[210],"additional":[212],"layers":[213],"were":[214],"added":[215],"fine":[217],"tuning.":[218],"results":[220],"demonstrate":[221],"model\u2019s":[223],"capacity":[224],"distinguish":[226],"diseased,":[230],"average":[233],"area":[234],"under":[235],"curve":[236],"(AUC)":[237],"0.99.":[239],"AUC":[241],"ranges":[242],"0.86":[244],"0.99":[248,252],"pneumonia":[250],"COVID-19.":[254],"Our":[255],"method":[256],"outperforms":[257],"state-of-the-art":[259],"accuracy":[261],"across":[262],"all":[263],"classes,":[265],"exception":[268],"consolidation,":[271],"mass,":[272],"nodule.":[274],"These":[275],"promising":[278],"tested":[281],"clinical":[282,288],"site,":[283],"though":[284],"further":[285],"validation":[286],"environment":[289],"accros":[290],"multiple":[291],"sites":[292],"be":[294],"before":[296],"using":[297],"model":[299],"standalone":[302],"decision":[303,308],"system,":[304],"rather":[305],"than":[306],"support":[309],"system":[310],"disease":[312],"based":[314],"on":[315]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-05-23T08:51:43.019350","created_date":"2025-10-10T00:00:00"}