{"id":"https://openalex.org/W4390098875","doi":"https://doi.org/10.1109/commnet60167.2023.10365251","title":"A New Architecture For Diagnosing Pulmonary Thorax Diseases (Covid-19, Pneumonology, Normal) Using Deep Learning Technology","display_name":"A New Architecture For Diagnosing Pulmonary Thorax Diseases (Covid-19, Pneumonology, Normal) Using Deep Learning Technology","publication_year":2023,"publication_date":"2023-12-11","ids":{"openalex":"https://openalex.org/W4390098875","doi":"https://doi.org/10.1109/commnet60167.2023.10365251"},"language":"en","primary_location":{"id":"doi:10.1109/commnet60167.2023.10365251","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/commnet60167.2023.10365251","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 6th International Conference on Advanced Communication Technologies and Networking (CommNet)","raw_type":"proceedings-article"},"type":"article","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/A5057899779","display_name":"Hammou Djalal Rafik","orcid":"https://orcid.org/0000-0002-0038-0424"},"institutions":[{"id":"https://openalex.org/I4210125514","display_name":"Universit\u00e9 Djilali de Sidi Bel Abb\u00e8s","ror":"https://ror.org/0378szg41","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210125514"]}],"countries":["DZ"],"is_corresponding":true,"raw_author_name":"Hammou Djalal Rafik","raw_affiliation_strings":["Djillali Liabes University,EEDIS,Department of computer sciences,Sidi Bel Abbes,Algeria,BP 89 22000"],"affiliations":[{"raw_affiliation_string":"Djillali Liabes University,EEDIS,Department of computer sciences,Sidi Bel Abbes,Algeria,BP 89 22000","institution_ids":["https://openalex.org/I4210125514"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093558853","display_name":"Yasmine Feddag Zoulikha","orcid":null},"institutions":[{"id":"https://openalex.org/I4210125514","display_name":"Universit\u00e9 Djilali de Sidi Bel Abb\u00e8s","ror":"https://ror.org/0378szg41","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210125514"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Yasmine Feddag Zoulikha","raw_affiliation_strings":["Djillali Liabes University,EEDIS,Department of computer sciences,Sidi Bel Abbes,Algeria,BP 89 22000"],"affiliations":[{"raw_affiliation_string":"Djillali Liabes University,EEDIS,Department of computer sciences,Sidi Bel Abbes,Algeria,BP 89 22000","institution_ids":["https://openalex.org/I4210125514"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052371061","display_name":"Benadane Samira","orcid":null},"institutions":[{"id":"https://openalex.org/I4210125514","display_name":"Universit\u00e9 Djilali de Sidi Bel Abb\u00e8s","ror":"https://ror.org/0378szg41","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210125514"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Benadane Samira","raw_affiliation_strings":["Djillali Liabes University,EEDIS,Department of computer sciences,Sidi Bel Abbes,Algeria,BP 89 22000"],"affiliations":[{"raw_affiliation_string":"Djillali Liabes University,EEDIS,Department of computer sciences,Sidi Bel Abbes,Algeria,BP 89 22000","institution_ids":["https://openalex.org/I4210125514"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057899779"],"corresponding_institution_ids":["https://openalex.org/I4210125514"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.38868214,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9998999834060669,"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":0.9998999834060669,"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9733999967575073,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9724000096321106,"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/thorax","display_name":"Thorax (insect anatomy)","score":0.6750650405883789},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5868600010871887},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.5689117312431335},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5420528054237366},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5282328128814697},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46189936995506287},{"id":"https://openalex.org/keywords/new-normal","display_name":"New normal","score":0.43409276008605957},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3913745880126953},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.2174399197101593},{"id":"https://openalex.org/keywords/anatomy","display_name":"Anatomy","score":0.17913585901260376},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.10751760005950928},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08917403221130371}],"concepts":[{"id":"https://openalex.org/C97834683","wikidata":"https://www.wikidata.org/wiki/Q942508","display_name":"Thorax (insect anatomy)","level":2,"score":0.6750650405883789},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5868600010871887},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.5689117312431335},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5420528054237366},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5282328128814697},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46189936995506287},{"id":"https://openalex.org/C2993273291","wikidata":"https://www.wikidata.org/wiki/Q16956210","display_name":"New normal","level":5,"score":0.43409276008605957},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3913745880126953},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.2174399197101593},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.17913585901260376},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.10751760005950928},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08917403221130371},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"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":[],"locations_count":1,"locations":[{"id":"doi:10.1109/commnet60167.2023.10365251","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/commnet60167.2023.10365251","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 6th International Conference on Advanced Communication Technologies and Networking (CommNet)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W160222701","https://openalex.org/W1534477342","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W2079479194","https://openalex.org/W2097117768","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2294567968","https://openalex.org/W2320641533","https://openalex.org/W2398921440","https://openalex.org/W2963446712","https://openalex.org/W3013277995","https://openalex.org/W3017141460","https://openalex.org/W3046575586","https://openalex.org/W3126486492","https://openalex.org/W3150298593","https://openalex.org/W3168715801","https://openalex.org/W3171873561","https://openalex.org/W3204607189","https://openalex.org/W4205586532","https://openalex.org/W4206067856","https://openalex.org/W4285404792","https://openalex.org/W4286384718","https://openalex.org/W4297775537","https://openalex.org/W4306377506","https://openalex.org/W4323044919","https://openalex.org/W4379534946","https://openalex.org/W4381137231","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6737664043"],"related_works":["https://openalex.org/W2527906156","https://openalex.org/W2385906609","https://openalex.org/W2368075107","https://openalex.org/W2391106160","https://openalex.org/W18538866","https://openalex.org/W4307092591","https://openalex.org/W4386178770","https://openalex.org/W4214662146","https://openalex.org/W1894726270","https://openalex.org/W4205698903"],"abstract_inverted_index":{"Medical":[0],"imaging":[1],"is":[2],"an":[3,141],"efficient":[4],"field":[5],"of":[6,43,47,60,114,140,154,159],"research":[7,57],"because":[8],"it":[9,11,53],"makes":[10],"possible":[12,54],"to":[13,27,37,55,78,97,125],"diagnose":[14,38],"and":[15,18,39,72,85,123,133,164,166,181],"detect":[16],"diseases":[17],"relieve":[19],"patients":[20],"by":[21,63],"presenting":[22],"a":[23,32,99,107,152],"remedy":[24],"or":[25],"treatment":[26],"follow.":[28],"Pulmonary":[29],"pathology":[30],"represents":[31],"principal":[33],"challenge":[34],"for":[35],"doctors":[36,67],"examine":[40],"the":[41,70,81,112,138],"type":[42],"disease.":[44],"The":[45,146],"use":[46],"medical":[48,61,83],"x-ray":[49],"images":[50,155],"has":[51],"made":[52],"advance":[56],"in":[58],"terms":[59],"findings":[62],"specialists.":[64],"Despite":[65],"this,":[66],"sometimes":[68],"misdiagnose":[69],"patient,":[71],"we":[73,95,167],"suggest":[74],"employing":[75],"artificial":[76],"intelligence":[77],"significantly":[79],"enhance":[80],"patient\u2019s":[82],"diagnosis":[84],"help":[86],"identify":[87],"lung":[88,160],"ailments":[89],"more":[90],"accurately.":[91],"In":[92],"this":[93,126],"project,":[94],"plan":[96],"develop":[98],"computer":[100],"system":[101],"based":[102,110],"on":[103,111,151,172],"deep":[104],"learning":[105],"with":[106,120,156],"coherent":[108],"approach":[109,171],"application":[113],"standard":[115],"convolutional":[116],"neural":[117],"networks":[118],"(CNN)":[119],"architectures":[121],"appropriate":[122],"specific":[124],"problem":[127],"(VGG16,":[128],"MobileNetV1,":[129],"ResNet50,":[130],"InceptionV3,":[131],"DenseNet121,":[132],"DenseNet169).":[134],"We":[135],"also":[136],"propose":[137],"construction":[139],"architectural":[142],"model":[143],"called":[144],"RafikNet.":[145],"tests":[147],"will":[148,168],"be":[149],"realized":[150],"corpus":[153],"three":[157],"types":[158],"disease":[161],"(COVID-19,":[162],"pneumology,":[163],"normals),":[165],"evaluate":[169],"our":[170],"parameters":[173],"such":[174],"as":[175],"accuracy,":[176],"precision,":[177],"recall,":[178],"f1-score,":[179],"support,":[180],"loss.":[182]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}
