{"id":"https://openalex.org/W2568622573","doi":"https://doi.org/10.1109/iecon.2016.7793954","title":"A novel SVM-RFE based biomedical data processing approach: Basic and beyond","display_name":"A novel SVM-RFE based biomedical data processing approach: Basic and beyond","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2568622573","doi":"https://doi.org/10.1109/iecon.2016.7793954","mag":"2568622573"},"language":"en","primary_location":{"id":"doi:10.1109/iecon.2016.7793954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon.2016.7793954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society","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/A5113758635","display_name":"Zuyu Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zuyu Yin","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111908775","display_name":"Zhongyang Fei","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongyang Fei","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083390109","display_name":"Chengming Yang","orcid":"https://orcid.org/0000-0003-3498-7352"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengming Yang","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100326788","display_name":"Ao Chen","orcid":"https://orcid.org/0000-0002-4848-9250"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ao Chen","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":null,"first_page":"7143","last_page":"7148"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.8573633432388306},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7129212617874146},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6918576955795288},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6724705100059509},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6386792659759521},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5899509787559509},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45358753204345703},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.44710758328437805},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4222370684146881},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3963809609413147},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11551091074943542}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8573633432388306},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7129212617874146},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6918576955795288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6724705100059509},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6386792659759521},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5899509787559509},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45358753204345703},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.44710758328437805},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4222370684146881},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3963809609413147},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11551091074943542},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iecon.2016.7793954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon.2016.7793954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1569369678","https://openalex.org/W1576894437","https://openalex.org/W1963802829","https://openalex.org/W1967358196","https://openalex.org/W1976610059","https://openalex.org/W1985512226","https://openalex.org/W1990283595","https://openalex.org/W2008616192","https://openalex.org/W2010685573","https://openalex.org/W2013872183","https://openalex.org/W2014374971","https://openalex.org/W2021252961","https://openalex.org/W2026039230","https://openalex.org/W2042561770","https://openalex.org/W2042584899","https://openalex.org/W2047622162","https://openalex.org/W2048660210","https://openalex.org/W2069914810","https://openalex.org/W2082969745","https://openalex.org/W2084172243","https://openalex.org/W2091087636","https://openalex.org/W2094040550","https://openalex.org/W2109965063","https://openalex.org/W2145114096","https://openalex.org/W2148603752","https://openalex.org/W2149298154","https://openalex.org/W2157157301","https://openalex.org/W2167453047","https://openalex.org/W2167618128","https://openalex.org/W2169347809","https://openalex.org/W4251036056","https://openalex.org/W6634506816","https://openalex.org/W6646698615"],"related_works":["https://openalex.org/W2579148721","https://openalex.org/W4387893611","https://openalex.org/W2347335694","https://openalex.org/W2091056927","https://openalex.org/W2067407580","https://openalex.org/W4317486777","https://openalex.org/W4389669152","https://openalex.org/W2038514069","https://openalex.org/W1967233468","https://openalex.org/W2009181529"],"abstract_inverted_index":{"Standard":[0],"support":[1],"vector":[2],"machine":[3],"(SVM)":[4],"serves":[5],"as":[6],"a":[7,40],"powerful":[8],"method":[9,22,41],"for":[10,15,31,156,162],"faults":[11],"diagnosis":[12],"and":[13,23,33,49,60,71,83,103,122,130],"classification":[14,32,81,132,165],"last":[16],"two":[17],"decades.":[18],"However,":[19],"this":[20,57,128],"standard":[21],"its":[24,163],"recent":[25],"versions":[26],"still":[27],"encounter":[28],"many":[29,138],"problems":[30],"diagnosis.":[34],"To":[35],"cope":[36],"with":[37,113],"these":[38],"problems,":[39],"(SVM-RFE)":[42],"combines":[43],"SVM,":[44],"recursive":[45],"feature":[46],"elimination":[47],"(RFE)":[48],"principal":[50],"component":[51],"analysis":[52],"(PCA)":[53],"is":[54,134],"presented":[55],"in":[56],"paper.":[58],"SVM-RFE":[59,121],"PCA":[61,123],"are":[62,86,99,124],"able":[63],"to":[64,90,101,127],"effectively":[65],"reduce":[66],"the":[67,73,80,92,95,105,131,147],"dimension":[68],"of":[69,94],"features":[70],"extract":[72],"most":[74],"relevant":[75],"features.":[76,115],"Based":[77],"on":[78],"them,":[79],"accuracy":[82,133],"calculation":[84],"speed":[85],"improved.":[87],"In":[88],"order":[89],"demonstrate":[91],"effectiveness":[93],"proposed":[96,148],"methods,":[97],"they":[98],"applied":[100,126],"diagnose":[102],"classify":[104],"Wisconsin":[106],"Diagnostic":[107],"Breast":[108],"Cancer":[109],"(WDBC)":[110],"data":[111,129],"sets":[112],"30":[114],"It":[116,142],"should":[117],"be":[118,144],"noticed":[119],"that":[120,146],"initially":[125],"much":[135],"better":[136],"than":[137],"other":[139],"researchers'":[140],"results.":[141],"can":[143],"seen":[145],"methods":[149],"show":[150],"satisfactory":[151],"simulation":[152],"results":[153],"not":[154],"only":[155],"diagnosing":[157],"breast":[158],"cancer":[159],"but":[160],"also":[161],"high":[164],"accuracy.":[166]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
