{"id":"https://openalex.org/W3033562213","doi":"https://doi.org/10.1145/3398329.3398337","title":"Improved Convolutional Neural Network for Lung Cancer Detection","display_name":"Improved Convolutional Neural Network for Lung Cancer Detection","publication_year":2020,"publication_date":"2020-04-24","ids":{"openalex":"https://openalex.org/W3033562213","doi":"https://doi.org/10.1145/3398329.3398337","mag":"3033562213"},"language":"en","primary_location":{"id":"doi:10.1145/3398329.3398337","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3398329.3398337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Conference on Computing, Networks and Internet of Things","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/A5031561816","display_name":"Firdaous Essaf","orcid":"https://orcid.org/0000-0002-9953-0372"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Firdaous Essaf","raw_affiliation_strings":["School of Computer Science and Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101457814","display_name":"Yujian Li","orcid":"https://orcid.org/0000-0002-4991-6461"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujian Li","raw_affiliation_strings":["School of Artificial Intelligence, Guilin University of Electronic Technology, Guilin, Guangxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Guilin University of Electronic Technology, Guilin, Guangxi, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019087796","display_name":"Seybou Sakho","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Seybou Sakho","raw_affiliation_strings":["School of Computer Science and Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057624061","display_name":"Pius Kwao Gadosey","orcid":"https://orcid.org/0000-0003-0454-274X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pius Kwao Gadosey","raw_affiliation_strings":["School of Computer Science and Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"48","last_page":"54"},"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":0.9973000288009644,"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":0.9973000288009644,"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9958999752998352,"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":0.9807999730110168,"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":0.8846359252929688},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7459890246391296},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6554749011993408},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.5878435373306274},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.564713716506958},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5367931127548218},{"id":"https://openalex.org/keywords/cad","display_name":"CAD","score":0.5113222599029541},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48944321274757385},{"id":"https://openalex.org/keywords/lung-cancer","display_name":"Lung cancer","score":0.4535178244113922},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.425418496131897},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.33180636167526245},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1771729290485382},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.1335921585559845}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8846359252929688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7459890246391296},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6554749011993408},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.5878435373306274},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.564713716506958},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5367931127548218},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.5113222599029541},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48944321274757385},{"id":"https://openalex.org/C2776256026","wikidata":"https://www.wikidata.org/wiki/Q47912","display_name":"Lung cancer","level":2,"score":0.4535178244113922},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.425418496131897},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.33180636167526245},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1771729290485382},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.1335921585559845},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3398329.3398337","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3398329.3398337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Conference on Computing, Networks and Internet of Things","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":0.6100000143051147}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1607519983","https://openalex.org/W1934410531","https://openalex.org/W1964812476","https://openalex.org/W1965468410","https://openalex.org/W1971076990","https://openalex.org/W2108981833","https://openalex.org/W2185802128","https://openalex.org/W2311857205","https://openalex.org/W2538033411","https://openalex.org/W2733646732","https://openalex.org/W2743008510","https://openalex.org/W2787067754","https://openalex.org/W2810094411","https://openalex.org/W2899675781","https://openalex.org/W2946281475","https://openalex.org/W2973061687","https://openalex.org/W2982625536","https://openalex.org/W3100321043","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2952813363","https://openalex.org/W4360783045"],"abstract_inverted_index":{"The":[0,93,127],"examination":[1],"of":[2,9,19,60,118,153],"the":[3,10,22,65,78,97,104,116,124,136,154],"lungs":[4,155],"is":[5,50,73,91,130,134],"an":[6],"important":[7],"part":[8],"annual":[11],"physical":[12,23],"examination.":[13],"There":[14],"are":[15],"hundreds":[16],"or":[17],"thousands":[18],"cases":[20,42],"in":[21,96],"examination,":[24],"and":[25,84,111,156],"each":[26],"case":[27],"contains":[28],"many":[29],"lung":[30],"cross-sectional":[31],"CT":[32,79,151],"images.":[33],"These":[34],"all":[35],"require":[36],"professional":[37],"doctors":[38],"to":[39,75],"screen":[40,76],"for":[41,81,163,171],"with":[43,103,142],"pulmonary":[44,82],"nodules":[45],"one":[46],"by":[47],"one,":[48],"which":[49,133],"not":[51],"only":[52],"a":[53,58,68,85,159],"heavy":[54],"workload":[55],"but":[56],"also":[57,135],"possibility":[59],"incorrect":[61],"screening.":[62],"Aiming":[63],"at":[64],"above":[66],"problems,":[67],"Convolutional":[69],"Neural":[70],"Network":[71],"(CNN)":[72],"introduced":[74],"out":[77],"images":[80,152],"nodules,":[83],"classification":[86,125],"algorithm":[87],"based":[88],"on":[89],"CNN":[90],"proposed.":[92],"experimental":[94],"results":[95],"LIDC":[98],"database":[99],"show":[100],"that":[101],"compared":[102],"widely":[105],"used":[106,170],"lenet-5":[107],"network,":[108],"traditional":[109],"methods,":[110,144],"other":[112,143],"deep":[113],"learning":[114],"models,":[115],"use":[117],"customized":[119],"convolutional":[120],"neural":[121],"networks":[122],"improves":[123],"accuracy.":[126],"AUC":[128],"value":[129],"0.821":[131],"6,":[132],"highest":[137],"among":[138],"several":[139],"classifiers.":[140],"Compared":[141],"this":[145],"method":[146],"can":[147,157,168],"more":[148,160],"accurately":[149],"identify":[150],"provide":[158],"objective":[161],"reference":[162],"clinical":[164],"diagnosis":[165],"as":[166],"it":[167],"be":[169],"CAD":[172],"systems.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
