{"id":"https://openalex.org/W2118263157","doi":"https://doi.org/10.1109/smcia.2001.936727","title":"New results in breast cancer classification obtained from an evolutionary computation/adaptive boosting hybrid using mammogram and history data","display_name":"New results in breast cancer classification obtained from an evolutionary computation/adaptive boosting hybrid using mammogram and history data","publication_year":2002,"publication_date":"2002-11-13","ids":{"openalex":"https://openalex.org/W2118263157","doi":"https://doi.org/10.1109/smcia.2001.936727","mag":"2118263157"},"language":"en","primary_location":{"id":"doi:10.1109/smcia.2001.936727","doi":"https://doi.org/10.1109/smcia.2001.936727","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smcia.2001.936727","pdf_url":null,"source":{"id":"https://openalex.org/S7407106546","display_name":"IEEE Conference on Soft Computing in Industrial Applications (SMCia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5103415805","display_name":"Walker H. Land","orcid":"https://orcid.org/0000-0002-8535-8276","observed_orcids":["https://orcid.org/0000-0002-8535-8276"]},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"W.H. Land","raw_affiliation_strings":["Binghamton University, Binghamton, NY, USA","[Binghamton University, NY, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Binghamton University, Binghamton, NY, USA","institution_ids":["https://openalex.org/I123946342"]},{"raw_affiliation_string":"[Binghamton University, NY, USA]","institution_ids":["https://openalex.org/I123946342"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036473782","display_name":"Timothy D. Masters","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"T. Masters","raw_affiliation_strings":["TMAIC, Brackney, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TMAIC, Brackney, PA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040192736","display_name":"Joseph Yuan-Chieh Lo","orcid":"https://orcid.org/0000-0002-9540-5072","observed_orcids":["https://orcid.org/0000-0002-9540-5072"]},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]},{"id":"https://openalex.org/I4210126298","display_name":"Duke Medical Center","ror":"https://ror.org/03njmea73","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210126298","https://openalex.org/I4210144876"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J.Y. Lo","raw_affiliation_strings":["Duke University Medical Center, Durham, NC, USA","Duke Univ. Medical Center, Durham, NC, USA,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University Medical Center, Durham, NC, USA","institution_ids":["https://openalex.org/I4210126298"]},{"raw_affiliation_string":"Duke Univ. Medical Center, Durham, NC, USA,","institution_ids":["https://openalex.org/I170897317","https://openalex.org/I4210126298"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054078662","display_name":"D.W. McKee","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D.W. McKee","raw_affiliation_strings":["Binghamton University, Binghamton, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Binghamton University, Binghamton, NY, USA","institution_ids":["https://openalex.org/I123946342"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111488490","display_name":"Frances R. Anderson","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210141890","display_name":"Lourdes Hospital","ror":"https://ror.org/040tgwz33","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210141890"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"F.R. Anderson","raw_affiliation_strings":["Our Lady of Lourdes, Memorial Hospital, Inc., Binghamton, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Our Lady of Lourdes, Memorial Hospital, Inc., Binghamton, NY, USA","institution_ids":["https://openalex.org/I4210141890"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6276,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.91732747,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":87,"max":95},"biblio":{"volume":"10","issue":null,"first_page":"47","last_page":"52"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9901999831199646,"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/T10862","display_name":"AI in cancer detection","score":0.9901999831199646,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.006399999838322401,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.0007999999797903001,"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/breast-cancer-classification","display_name":"breast cancer classification","score":0.9229999780654907},{"id":"https://openalex.org/keywords/mammography","display_name":"mammography","score":0.746999979019165},{"id":"https://openalex.org/keywords/adaptive-boosting","display_name":"adaptive boosting","score":0.9620000123977661},{"id":"https://openalex.org/keywords/evolutionary-programming","display_name":"evolutionary programming","score":0.9309999942779541},{"id":"https://openalex.org/keywords/hybrid-neural-network","display_name":"hybrid neural network","score":0.7590000033378601},{"id":"https://openalex.org/keywords/weak-learning","display_name":"weak learning","score":0.7300000190734863},{"id":"https://openalex.org/keywords/diagnostic-specificity","display_name":"diagnostic specificity","score":0.5270000100135803},{"id":"https://openalex.org/keywords/positive-predictive-value","display_name":"positive predictive value","score":0.9929999709129333},{"id":"https://openalex.org/keywords/breast-cancer-diagnosis","display_name":"breast cancer diagnosis","score":0.531000018119812}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8219701051712036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7258139848709106},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6630662679672241},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6611494421958923},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6198960542678833},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.4866955578327179},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.43076062202453613},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3637274503707886},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.16633421182632446},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.07754144072532654},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smcia.2001.936727","doi":"https://doi.org/10.1109/smcia.2001.936727","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smcia.2001.936727","pdf_url":null,"source":{"id":"https://openalex.org/S7407106546","display_name":"IEEE Conference on Soft Computing in Industrial Applications (SMCia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.5683000087738037}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1978970913","https://openalex.org/W1988790447","https://openalex.org/W1993518750","https://openalex.org/W2019363670","https://openalex.org/W2032210760","https://openalex.org/W2035005104","https://openalex.org/W2058059827","https://openalex.org/W2070534370","https://openalex.org/W2070718488","https://openalex.org/W2081824827","https://openalex.org/W2093717447","https://openalex.org/W2124152802","https://openalex.org/W2141900712","https://openalex.org/W2142399242","https://openalex.org/W2284330674","https://openalex.org/W3034905139","https://openalex.org/W4238893454","https://openalex.org/W4244952642"],"related_works":["https://openalex.org/W2048733178","https://openalex.org/W2141900712","https://openalex.org/W1921211821","https://openalex.org/W1791903561","https://openalex.org/W2027612884","https://openalex.org/W2116824390","https://openalex.org/W1976092880","https://openalex.org/W1980515656","https://openalex.org/W2018719312","https://openalex.org/W2138539097"],"abstract_inverted_index":{"A":[0],"new":[1,36],"neural":[2,88],"network":[3,89],"technology":[4],"was":[5,152],"developed":[6],"to":[7,49,154],"improve":[8],"the":[9,29,72,76,83,129,132,139],"diagnosis":[10],"of":[11,68,82,93,128,131,143,162,170,181,186],"breast":[12],"cancer":[13],"using":[14,105],"mammogram":[15,62,73,109,141],"findings.":[16],"The":[17,91],"paradigm,":[18,39],"adaptive":[19,77],"boosting":[20,78],"(AB),":[21],"uses":[22],"a":[23,35,61,106,160,165,179,184],"markedly":[24],"different":[25],"theory":[26],"in":[27],"solving":[28],"computational":[30],"intelligence":[31],"(CI)":[32],"problem.":[33],"AB,":[34],"machine":[37],"learning":[38,44],"focuses":[40],"on":[41,114,150],"finding":[42],"weak":[43],"algorithm(s)":[45],"that":[46],"initially":[47],"need":[48],"provide":[50],"slightly":[51],"better":[52],"than":[53],"\"random\"":[54],"performance":[55,81,130],"(i.e.,":[56],"approximately":[57],"55%)":[58],"when":[59],"processing":[60],"training":[63,74],"set.":[64,111],"By":[65],"successive":[66],"development":[67],"additional":[69],"architectures":[70,98],"(using":[71],"set),":[75],"process":[79],"improves":[80],"basic":[84],"evolutionary":[85],"programming":[86],"derived":[87],"architectures.":[90],"results":[92],"these":[94],"several":[95],"EP-derived":[96],"hybrid":[97,133],"are":[99],"then":[100],"intelligently":[101],"combined":[102],"and":[103,117,164,183],"tested":[104],"similar":[107],"validation":[108],"data":[110],"Optimization,":[112],"focused":[113],"improving":[115],"specificity":[116,161,180],"positive":[118,166],"predictive":[119,167],"value":[120,168],"at":[121],"very":[122],"high":[123],"sensitivities,":[124],"with":[125],"an":[126],"analysis":[127],"would":[134],"be":[135],"most":[136],"meaningful.":[137],"Using":[138],"DUKE":[140],"database":[142],"500":[144],"biopsy":[145],"proven":[146],"samples,":[147],"this":[148],"hybrid,":[149],"average,":[151],"able":[153],"achieve":[155],"(under":[156],"statistical":[157],"5-fold":[158],"cross-validation)":[159],"48.3%":[163],"(PPV)":[169],"51.8%":[171],"while":[172],"maintaining":[173],"100%":[174],"sensitivity.":[175],"At":[176],"97%":[177],"sensitivity,":[178],"56.6%":[182],"PPV":[185],"55.8%":[187],"were":[188],"obtained.":[189]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}
