{"id":"https://openalex.org/W2909082165","doi":"https://doi.org/10.1109/access.2019.2892795","title":"Breast Cancer Detection Using Extreme Learning Machine Based on Feature Fusion With CNN Deep Features","display_name":"Breast Cancer Detection Using Extreme Learning Machine Based on Feature Fusion With CNN Deep Features","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2909082165","doi":"https://doi.org/10.1109/access.2019.2892795","mag":"2909082165"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2892795","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2892795","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08613773.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08613773.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103215657","display_name":"Zhiqiong Wang","orcid":"https://orcid.org/0000-0002-0095-0378"},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiong Wang","raw_affiliation_strings":["Neusoft Research of Intelligent Healthcare Technology, Co. Ltd., Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Neusoft Research of Intelligent Healthcare Technology, Co. Ltd., Shenyang, China","institution_ids":["https://openalex.org/I4210134419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361464","display_name":"Mo Li","orcid":"https://orcid.org/0000-0002-8943-0191"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mo Li","raw_affiliation_strings":["Key Laboratory of Big Data Management and Analytics (Liaoning), School of Computer Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-8943-0191","affiliations":[{"raw_affiliation_string":"Key Laboratory of Big Data Management and Analytics (Liaoning), School of Computer Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031877375","display_name":"Huaxia Wang","orcid":"https://orcid.org/0000-0002-3273-6309"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huaxia Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068100390","display_name":"Hanyu Jiang","orcid":"https://orcid.org/0000-0002-7827-0719"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hanyu Jiang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021827481","display_name":"Yudong Yao","orcid":"https://orcid.org/0000-0003-3868-0593"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yudong Yao","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA"],"raw_orcid":"https://orcid.org/0000-0003-3868-0593","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100396804","display_name":"Hao Zhang","orcid":"https://orcid.org/0009-0001-8603-2526"},"institutions":[{"id":"https://openalex.org/I91656880","display_name":"China Medical University","ror":"https://ror.org/032d4f246","country_code":"CN","type":"education","lineage":["https://openalex.org/I91656880"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhang","raw_affiliation_strings":["Department of Breast Surgery, Shengjing Hospital of China Medical University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Breast Surgery, Shengjing Hospital of China Medical University, Shenyang, China","institution_ids":["https://openalex.org/I91656880"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087247680","display_name":"Junchang Xin","orcid":"https://orcid.org/0000-0003-2077-8269"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junchang Xin","raw_affiliation_strings":["Key Laboratory of Big Data Management and Analytics (Liaoning), School of Computer Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0003-2077-8269","affiliations":[{"raw_affiliation_string":"Key Laboratory of Big Data Management and Analytics (Liaoning), School of Computer Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":22.1667,"has_fulltext":true,"cited_by_count":349,"citation_normalized_percentile":{"value":0.99542397,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"7","issue":null,"first_page":"105146","last_page":"105158"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9979000091552734,"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"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9979000091552734,"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"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9969000220298767,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8327049612998962},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7794865965843201},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.738838791847229},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7208148837089539},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7089152336120605},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6249659061431885},{"id":"https://openalex.org/keywords/cad","display_name":"CAD","score":0.6089408993721008},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5377246737480164},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5174294114112854},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4933423101902008},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.46557849645614624},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.44283556938171387},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4174679219722748},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38350802659988403},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.20176300406455994}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8327049612998962},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7794865965843201},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.738838791847229},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7208148837089539},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7089152336120605},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6249659061431885},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.6089408993721008},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5377246737480164},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5174294114112854},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4933423101902008},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.46557849645614624},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.44283556938171387},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4174679219722748},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38350802659988403},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.20176300406455994},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2892795","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2892795","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08613773.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3f07ad5a96c648ecafa00161d1a5f9a9","is_oa":true,"landing_page_url":"https://doaj.org/article/3f07ad5a96c648ecafa00161d1a5f9a9","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":"IEEE Access, Vol 7, Pp 105146-105158 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2892795","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2892795","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08613773.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.7699999809265137,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G3156078161","display_name":null,"funder_award_id":"2018M641705","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3372369086","display_name":null,"funder_award_id":"N161904001","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4044104431","display_name":null,"funder_award_id":"U1401256","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5277818219","display_name":null,"funder_award_id":"2018M641705","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G5369582884","display_name":null,"funder_award_id":"61402089","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7454390550","display_name":null,"funder_award_id":"N160601001","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7662411815","display_name":null,"funder_award_id":"N161602003","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8453870523","display_name":null,"funder_award_id":"61472069","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1973235766","https://openalex.org/W1973996862","https://openalex.org/W1984020445","https://openalex.org/W1988819287","https://openalex.org/W1992912731","https://openalex.org/W2011652426","https://openalex.org/W2033262494","https://openalex.org/W2042184006","https://openalex.org/W2073046599","https://openalex.org/W2077819016","https://openalex.org/W2101771332","https://openalex.org/W2106596998","https://openalex.org/W2111072639","https://openalex.org/W2120580182","https://openalex.org/W2131062842","https://openalex.org/W2131148034","https://openalex.org/W2147297736","https://openalex.org/W2150453191","https://openalex.org/W2150461190","https://openalex.org/W2151281402","https://openalex.org/W2159010619","https://openalex.org/W2167866422","https://openalex.org/W2178957972","https://openalex.org/W2200566924","https://openalex.org/W2284539364","https://openalex.org/W2299565249","https://openalex.org/W2317417577","https://openalex.org/W2492170386","https://openalex.org/W2559553341","https://openalex.org/W2571012593","https://openalex.org/W2605960745","https://openalex.org/W2744692634","https://openalex.org/W2752169992","https://openalex.org/W2755798823","https://openalex.org/W2755855890","https://openalex.org/W2773886975","https://openalex.org/W2779077044","https://openalex.org/W2802761519","https://openalex.org/W4250628002"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W31566076","https://openalex.org/W4297902562","https://openalex.org/W2741186499","https://openalex.org/W2804652951","https://openalex.org/W2968645206","https://openalex.org/W2556335056","https://openalex.org/W2002678693","https://openalex.org/W2472390602","https://openalex.org/W4309346246"],"abstract_inverted_index":{"A":[0],"computer-aided":[1],"diagnosis":[2],"(CAD)":[3],"system":[4],"based":[5,33,51],"on":[6,34,52],"mammograms":[7],"enables":[8],"early":[9],"breast":[10,30,95,110],"cancer":[11,111],"detection,":[12],"diagnosis,":[13],"and":[14,56,76,93,102,109],"treatment.":[15],"However,":[16],"the":[17,20,86,100],"accuracy":[18,101],"of":[19,104],"existing":[21],"CAD":[22,31],"systems":[23],"remains":[24],"unsatisfactory.":[25],"This":[26],"paper":[27],"explores":[28],"a":[29,47,66],"method":[32,50],"feature":[35,67,88],"fusion":[36],"with":[37],"convolutional":[38],"neural":[39],"network":[40],"(CNN)":[41],"deep":[42,54,70],"features.":[43,78],"First,":[44],"we":[45,64],"propose":[46],"mass":[48,107],"detection":[49,108],"CNN":[53],"features":[55],"unsupervised":[57],"extreme":[58],"learning":[59],"machine":[60],"(ELM)":[61],"clustering.":[62],"Second,":[63],"build":[65],"set":[68,89],"fusing":[69],"features,":[71,73,75],"morphological":[72],"texture":[74],"density":[77],"Third,":[79],"an":[80],"ELM":[81],"classifier":[82],"is":[83],"developed":[84],"using":[85],"fused":[87],"to":[90],"classify":[91],"benign":[92],"malignant":[94],"masses.":[96],"Extensive":[97],"experiments":[98],"demonstrate":[99],"efficiency":[103],"our":[105],"proposed":[106],"classification":[112],"method.":[113]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":32},{"year":2024,"cited_by_count":58},{"year":2023,"cited_by_count":89},{"year":2022,"cited_by_count":65},{"year":2021,"cited_by_count":58},{"year":2020,"cited_by_count":29},{"year":2019,"cited_by_count":5}],"updated_date":"2026-05-19T21:40:30.786675","created_date":"2025-10-10T00:00:00"}
