{"id":"https://openalex.org/W4410537381","doi":"https://doi.org/10.1109/ssd64182.2025.10989927","title":"Lung Disease Classification in X-ray Images using a Modified Deep Convolutional Neural Networks","display_name":"Lung Disease Classification in X-ray Images using a Modified Deep Convolutional Neural Networks","publication_year":2025,"publication_date":"2025-02-17","ids":{"openalex":"https://openalex.org/W4410537381","doi":"https://doi.org/10.1109/ssd64182.2025.10989927"},"language":"en","primary_location":{"id":"doi:10.1109/ssd64182.2025.10989927","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd64182.2025.10989927","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 22nd International Multi-Conference on Systems, Signals & Devices (SSD)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"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/A5010273089","display_name":"Ines Chouat","orcid":null},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Ines Chouat","raw_affiliation_strings":["National Engineering School of Sfax (ENIS), Sfax University,Advanced Technologies for Medicine and Signals Laboratory ‘ATMS’,Sfax,Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Engineering School of Sfax (ENIS), Sfax University,Advanced Technologies for Medicine and Signals Laboratory ‘ATMS’,Sfax,Tunisia","institution_ids":["https://openalex.org/I142899784"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019600021","display_name":"Amira Echtioui","orcid":"https://orcid.org/0000-0003-2041-1301"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Amira Echtioui","raw_affiliation_strings":["National Engineering School of Sfax (ENIS), Sfax University,Advanced Technologies for Medicine and Signals Laboratory ‘ATMS’,Sfax,Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Engineering School of Sfax (ENIS), Sfax University,Advanced Technologies for Medicine and Signals Laboratory ‘ATMS’,Sfax,Tunisia","institution_ids":["https://openalex.org/I142899784"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074703787","display_name":"Mohamed Ghorbel","orcid":"https://orcid.org/0000-0003-0821-0398"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Mohamed Ghorbel","raw_affiliation_strings":["National Engineering School of Sfax (ENIS), Sfax University,Advanced Technologies for Medicine and Signals Laboratory ‘ATMS’,Sfax,Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Engineering School of Sfax (ENIS), Sfax University,Advanced Technologies for Medicine and Signals Laboratory ‘ATMS’,Sfax,Tunisia","institution_ids":["https://openalex.org/I142899784"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I142899784"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1009","last_page":"1014"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.8748999834060669,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.8748999834060669,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.8411999940872192,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7914948463439941},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6917898058891296},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6432529091835022},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45461758971214294},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45249104499816895},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4233905076980591},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13767686486244202}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7914948463439941},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6917898058891296},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6432529091835022},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45461758971214294},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45249104499816895},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4233905076980591},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13767686486244202}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssd64182.2025.10989927","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd64182.2025.10989927","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 22nd International Multi-Conference on Systems, Signals & Devices (SSD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2897806204","https://openalex.org/W2962975664","https://openalex.org/W2983132969","https://openalex.org/W3013813478","https://openalex.org/W3016292699","https://openalex.org/W3033616466","https://openalex.org/W3064374686","https://openalex.org/W3090304925","https://openalex.org/W3090754826","https://openalex.org/W3133191822","https://openalex.org/W4317435715","https://openalex.org/W4353083551","https://openalex.org/W4376128796","https://openalex.org/W4383888035","https://openalex.org/W4393948187","https://openalex.org/W4405272350","https://openalex.org/W6637345178","https://openalex.org/W6784672455"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W4226493464","https://openalex.org/W3215138031","https://openalex.org/W3133861977","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W2951211570","https://openalex.org/W3103566983"],"abstract_inverted_index":{"Diagnosing":[0],"lung":[1,36,173,182],"diseases":[2,37,183],"is":[3],"a":[4,39,169],"complex":[5],"process":[6],"that":[7,138],"requires":[8],"the":[9,99,109,122,141,164,194],"integration":[10],"of":[11,35,51,108,124,147,150,153,159,166,196],"clinical":[12,217],"data,":[13],"including":[14],"test":[15],"results,":[16],"medical":[17,23,189,203],"history,":[18],"and":[19,30,48,77,105,132,155,184,212],"patient":[20,214],"symptoms,":[21],"with":[22,85,202],"imaging":[24],"modalities":[25],"such":[26,74],"as":[27,59,75,168],"CT":[28],"scans":[29],"X-rays.":[31],"The":[32,134],"accurate":[33],"classification":[34],"plays":[38],"pivotal":[40],"role":[41],"in":[42,62,216],"healthcare":[43],"by":[44,102],"enabling":[45],"precise":[46],"diagnosis":[47],"effective":[49],"treatment":[50],"various":[52],"conditions.":[53,190],"Deep":[54],"learning":[55,200],"models":[56],"have":[57],"emerged":[58],"valuable":[60],"tools":[61],"this":[63,113],"domain,":[64],"leveraging":[65],"large":[66],"datasets":[67],"to":[68,97,120,179],"improve":[69],"diagnostic":[70],"accuracy.":[71],"Nevertheless,":[72],"challenges":[73],"overfitting":[76],"limited":[78],"generalization":[79],"remain":[80],"prevalent,":[81],"particularly":[82],"when":[83],"working":[84],"small":[86],"datasets.":[87],"To":[88],"mitigate":[89],"these":[90],"issues,":[91],"data":[92,115],"augmentation":[93,116],"techniques":[94],"are":[95],"employed":[96],"expand":[98],"training":[100],"dataset":[101],"generating":[103],"diverse":[104],"realistic":[106],"variations":[107],"available":[110],"samples.":[111],"In":[112],"study,":[114],"strategies":[117],"were":[118],"applied":[119],"evaluate":[121],"performance":[123],"three":[125],"pre-trained":[126],"deep":[127,199],"neural":[128],"networks:":[129],"VGG-16,":[130],"DenseNet-121,":[131],"DenseNet-201.":[133],"comparative":[135],"analysis":[136],"revealed":[137],"DenseNet-201":[139,167],"outperformed":[140],"other":[142,188],"models,":[143],"achieving":[144],"an":[145,156],"accuracy":[146],"83%,":[148],"precision":[149],"80.25%,":[151],"recall":[152],"79%,":[154],"F1":[157],"score":[158],"78.75%.":[160],"These":[161],"results":[162],"highlight":[163],"potential":[165],"robust":[170],"model":[171],"for":[172,208],"disease":[174,210],"classification,":[175],"demonstrating":[176],"its":[177],"ability":[178],"accurately":[180],"identify":[181],"differentiate":[185],"them":[186],"from":[187],"This":[191],"study":[192],"underscores":[193],"significance":[195],"integrating":[197],"advanced":[198],"methodologies":[201],"diagnostics,":[204],"offering":[205],"promising":[206],"implications":[207],"enhancing":[209],"recognition":[211],"improving":[213],"care":[215],"settings.":[218]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}