{"id":"https://openalex.org/W2292693580","doi":"https://doi.org/10.1115/1.802655.paper6","title":"Performance Validation Using Several Statistical Learning Theory Paradigms for Mammogram Screen Film and Clinical Data Features","display_name":"Performance Validation Using Several Statistical Learning Theory Paradigms for Mammogram Screen Film and Clinical Data Features","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2292693580","doi":"https://doi.org/10.1115/1.802655.paper6","mag":"2292693580"},"language":"en","primary_location":{"id":"doi:10.1115/1.802655.paper6","doi":"https://doi.org/10.1115/1.802655.paper6","is_oa":false,"landing_page_url":"https://doi.org/10.1115/1.802655.paper6","pdf_url":null,"source":{"id":"https://openalex.org/S4306462865","display_name":"ASME Press eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17","raw_type":"book-chapter"},"volume":{"id":"https://openalex.org/W2916162316","display_name":"Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17"},"type":"book-chapter","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":[],"countries":[],"is_corresponding":false,"raw_author_name":"Land, Walker H.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019238107","display_name":"George Tomko","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tomko, George","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5081098585","display_name":"John Heine","orcid":"https://orcid.org/0000-0003-1967-0701","observed_orcids":["https://orcid.org/0000-0003-1967-0701"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heine, John","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18833034,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"37","last_page":"42"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.8324999809265137,"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":0.8324999809265137,"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":0.14640000462532043,"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":0.004100000020116568,"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-diagnosis","display_name":"breast cancer diagnosis","score":0.9639999866485596},{"id":"https://openalex.org/keywords/statistical-learning-theory","display_name":"statistical learning theory","score":0.9229999780654907},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.8489999771118164},{"id":"https://openalex.org/keywords/evolutionary-programming","display_name":"evolutionary programming","score":0.9599999785423279},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"logistic regression","score":0.9509999752044678},{"id":"https://openalex.org/keywords/chi-square-feature-selection","display_name":"chi-square feature selection","score":0.8330000042915344},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"receiver operating characteristic","score":0.7739999890327454},{"id":"https://openalex.org/keywords/diagnostic-accuracy","display_name":"diagnostic accuracy","score":0.5960000157356262},{"id":"https://openalex.org/keywords/breast-composition","display_name":"breast tissue composition","score":0.7590000033378601},{"id":"https://openalex.org/keywords/family-history-medicine","display_name":"family history (medicine)","score":0.8489999771118164}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7720786929130554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6313477158546448},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.569456160068512},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5271225571632385},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5057439804077148},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4919860064983368},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.48408520221710205},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.4383179247379303},{"id":"https://openalex.org/C2982736386","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Statistical learning","level":2,"score":0.42592257261276245},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4241543412208557},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.4068520963191986},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3654976189136505},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32059919834136963},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2538769245147705},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23887449502944946},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.16044911742210388},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09344211220741272},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1115/1.802655.paper6","doi":"https://doi.org/10.1115/1.802655.paper6","is_oa":false,"landing_page_url":"https://doi.org/10.1115/1.802655.paper6","pdf_url":null,"source":{"id":"https://openalex.org/S4306462865","display_name":"ASME Press eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.46810001134872437,"display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W104605359","https://openalex.org/W2066926558","https://openalex.org/W246300693","https://openalex.org/W2025208635","https://openalex.org/W2056612643","https://openalex.org/W2048660210","https://openalex.org/W4234566826","https://openalex.org/W1980515656","https://openalex.org/W2373139759","https://openalex.org/W7133337043"],"abstract_inverted_index":{"In":[0],"an":[1],"ANNIE":[2,29],"2006":[3],"paper":[4,79],"\"Comparison":[5],"of":[6,28],"Logistics":[7],"Regression":[8],"(LR)":[9],"and":[10,18,41,53,70,93],"Evolutionary":[11,42],"Programming":[12,43],"derived":[13,21,44],"Support":[14],"Vector":[15],"Machines":[16],"(EP-SVMs)":[17],"CHI":[19],"Squared":[20],"results":[22],"for":[23,35],"breast":[24,67],"cancer":[25],"diagnosis\",":[26],"pp267\u2013272":[27],"volume":[30],"16,":[31],"it":[32,62],"was":[33,63],"demonstrated":[34],"the":[36,48,85,89],"first":[37],"time":[38],"that":[39,66,81],"LR":[40],"SVMs":[45],"provided":[46],"essentially":[47],"same":[49,90],"diagnostic":[50,76],"accuracy":[51],"using":[52],"ROC":[54],"analysis.":[55],"However,":[56],"in":[57],"a":[58],"surprising":[59],"preliminary":[60],"finding,":[61],"also":[64],"shown":[65],"composition,":[68],"age":[69],"family":[71],"history":[72],"are":[73],"not":[74],"significant":[75],"discriminators.":[77],"This":[78],"extends":[80],"research":[82],"by":[83],"investigating":[84],"performance":[86],"results,":[87],"employing":[88],"data":[91],"set":[92],"statistical":[94],"cross":[95],"validation":[96],"methods,":[97],"using,":[98],"in...":[99]},"counts_by_year":[],"updated_date":"2026-10-10T09:11:00.788812","created_date":"2016-06-24T00:00:00"}