{"id":"https://openalex.org/W4309400200","doi":"https://doi.org/10.1109/pais56586.2022.9946875","title":"A deep-based compound model for lung cancer detection","display_name":"A deep-based compound model for lung cancer detection","publication_year":2022,"publication_date":"2022-10-12","ids":{"openalex":"https://openalex.org/W4309400200","doi":"https://doi.org/10.1109/pais56586.2022.9946875"},"language":"en","primary_location":{"id":"doi:10.1109/pais56586.2022.9946875","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pais56586.2022.9946875","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS)","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/A5005481350","display_name":"Sourour Maalem","orcid":"https://orcid.org/0000-0003-0588-3087"},"institutions":[{"id":"https://openalex.org/I4210131710","display_name":"\u00c9cole Normale Sup\u00e9rieure de Constantine","ror":"https://ror.org/03xz4j444","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210131710"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Sourour Maalem","raw_affiliation_strings":["ENS Constantine,Dept. Computer Science and Maths,Algeria","Dept. Computer Science and Maths, ENS Constantine, Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ENS Constantine,Dept. Computer Science and Maths,Algeria","institution_ids":["https://openalex.org/I4210131710"]},{"raw_affiliation_string":"Dept. Computer Science and Maths, ENS Constantine, Algeria","institution_ids":["https://openalex.org/I4210131710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091709785","display_name":"Mohammed Mounir Bouhamed","orcid":"https://orcid.org/0000-0002-4171-8604"},"institutions":[{"id":"https://openalex.org/I125485651","display_name":"University Fr\u00e8res Mentouri Constantine 1","ror":"https://ror.org/017wv6808","country_code":"DZ","type":"education","lineage":["https://openalex.org/I125485651"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Mohammed Mounir Bouhamed","raw_affiliation_strings":["Constantine 2 university,MISC Laboratory,Algeria","MISC Laboratory, Constantine 2 university, Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Constantine 2 university,MISC Laboratory,Algeria","institution_ids":["https://openalex.org/I125485651"]},{"raw_affiliation_string":"MISC Laboratory, Constantine 2 university, Algeria","institution_ids":["https://openalex.org/I125485651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028217200","display_name":"Mohamed Gasmi","orcid":"https://orcid.org/0000-0001-5872-9142"},"institutions":[{"id":"https://openalex.org/I4210095290","display_name":"Universit\u00e9 Larbi T\u00e9bessi","ror":"https://ror.org/00tnac320","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210095290"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Mohamed Gasmi","raw_affiliation_strings":["Tebessa university,LRS Laboratory,Algeria","LRS Laboratory, Tebessa university, Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tebessa university,LRS Laboratory,Algeria","institution_ids":["https://openalex.org/I4210095290"]},{"raw_affiliation_string":"LRS Laboratory, Tebessa university, Algeria","institution_ids":["https://openalex.org/I4210095290"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.5686,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.91013487,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9926000237464905,"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"}},"topics":[{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9926000237464905,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9904000163078308,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9596999883651733,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7741820216178894},{"id":"https://openalex.org/keywords/lung-cancer","display_name":"Lung cancer","score":0.7096662521362305},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6279993057250977},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6108341813087463},{"id":"https://openalex.org/keywords/malignancy","display_name":"Malignancy","score":0.584763765335083},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.5091759562492371},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.5083038210868835},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.508112907409668},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49289751052856445},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.4423292577266693},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.4299306869506836},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4282112121582031},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4237586557865143},{"id":"https://openalex.org/keywords/medical-physics","display_name":"Medical physics","score":0.3993721008300781},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.37284189462661743},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.15789595246315002},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.08702781796455383}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7741820216178894},{"id":"https://openalex.org/C2776256026","wikidata":"https://www.wikidata.org/wiki/Q47912","display_name":"Lung cancer","level":2,"score":0.7096662521362305},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6279993057250977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6108341813087463},{"id":"https://openalex.org/C2779399171","wikidata":"https://www.wikidata.org/wiki/Q1483951","display_name":"Malignancy","level":2,"score":0.584763765335083},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.5091759562492371},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.5083038210868835},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.508112907409668},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49289751052856445},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.4423292577266693},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.4299306869506836},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4282112121582031},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4237586557865143},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.3993721008300781},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.37284189462661743},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.15789595246315002},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.08702781796455383},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pais56586.2022.9946875","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pais56586.2022.9946875","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1829852423","https://openalex.org/W2081101007","https://openalex.org/W2136177244","https://openalex.org/W2530907666","https://openalex.org/W2551336426","https://openalex.org/W2883386903","https://openalex.org/W2894536695","https://openalex.org/W2903224300","https://openalex.org/W3001403235","https://openalex.org/W3031060177","https://openalex.org/W3125261485","https://openalex.org/W3135294353","https://openalex.org/W3137043462","https://openalex.org/W3137567949","https://openalex.org/W3186345593","https://openalex.org/W3209312211","https://openalex.org/W3209740126","https://openalex.org/W3210816447","https://openalex.org/W4200362451","https://openalex.org/W4226110923","https://openalex.org/W4248815198","https://openalex.org/W4285124586","https://openalex.org/W4286377357","https://openalex.org/W4294558040","https://openalex.org/W4294691651","https://openalex.org/W6728304382","https://openalex.org/W6734026524","https://openalex.org/W6803196710","https://openalex.org/W6843107192"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W3024479225","https://openalex.org/W4323287533","https://openalex.org/W3171371563","https://openalex.org/W4360994352"],"abstract_inverted_index":{"<tex":[0],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[1],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$X$</tex>":[2],"-ray":[3],"image":[4],"analysis":[5],"is":[6],"primarily":[7],"performed":[8],"by":[9,140],"medical":[10,156],"specialists.":[11],"Patients":[12],"expect":[13],"a":[14,39,148,151],"correct":[15],"interpretation":[16,30],"of":[17,21,26,31,72,80,82,98,143],"these":[18],"images":[19],"regardless":[20],"cost.":[22],"Despite":[23],"various":[24],"advantages":[25],"chest":[27],"radiography,":[28],"the":[29,43,46,53,69,85,95,115,123,141,144],"Magnetic":[32],"Resonance":[33],"Imaging":[34],"(MRI)":[35],"has":[36],"always":[37],"been":[38],"major":[40],"issue":[41],"for":[42,155],"physician":[44],"and":[45,78,106],"radiologist":[47],"due":[48],"to":[49,52,104,137],"misdiagnosis.":[50],"According":[51],"World":[54],"Health":[55],"Organization,":[56],"Lung":[57],"cancer":[58,73,109],"cost":[59],"around":[60],"1.8":[61],"million":[62],"deaths":[63],"in":[64],"2020,":[65],"which":[66,146],"makes":[67],"it":[68],"leading":[70],"cause":[71],"death":[74],"worldwide.":[75],"Late":[76],"diagnosis":[77],"lack":[79],"means":[81],"screening":[83],"are":[84],"main":[86],"problems.":[87],"The":[88],"algorithm":[89,120],"can":[90],"help":[91],"radiologists":[92],"accurately":[93],"estimate":[94],"malignancy":[96],"risk":[97],"lung":[99,108],"nodules.":[100],"This":[101],"paper":[102],"aims":[103],"detect":[105],"classify":[107],"using":[110],"deep":[111],"learning.":[112],"We":[113],"used":[114],"Convolutional":[116],"Neural":[117],"Network":[118],"(CNN)":[119],"combined":[121],"with":[122,126,150],"Faster":[124],"Regions":[125],"CNN":[127],"(Fast":[128],"R-CNN).":[129],"Our":[130],"model":[131,149],"provides":[132,147],"very":[133],"encouraging":[134],"results":[135],"compared":[136],"those":[138],"obtained":[139],"work":[142],"literature,":[145],"high":[152],"accuracy":[153],"rate":[154],"assistance.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}