{"id":"https://openalex.org/W2596528911","doi":"https://doi.org/10.1117/12.2268406","title":"Abnormal cervical cell detection based on an adaptive margin-based feature selection method","display_name":"Abnormal cervical cell detection based on an adaptive margin-based feature selection method","publication_year":2017,"publication_date":"2017-03-17","ids":{"openalex":"https://openalex.org/W2596528911","doi":"https://doi.org/10.1117/12.2268406","mag":"2596528911"},"language":"en","primary_location":{"id":"doi:10.1117/12.2268406","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2268406","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},"type":"article","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/A5102841027","display_name":"Lili Zhao","orcid":"https://orcid.org/0000-0002-0634-0482"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lili Zhao","raw_affiliation_strings":["National Univ. of Defense Technology (China)"],"affiliations":[{"raw_affiliation_string":"National Univ. of Defense Technology (China)","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100723030","display_name":"Kuan Li","orcid":"https://orcid.org/0000-0002-3272-4084"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kuan Li","raw_affiliation_strings":["National Univ. of Defense Technology (China)"],"affiliations":[{"raw_affiliation_string":"National Univ. of Defense Technology (China)","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047935086","display_name":"Hongyun Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyun Yang","raw_affiliation_strings":["National Univ. of Defense Technology (China)"],"affiliations":[{"raw_affiliation_string":"National Univ. of Defense Technology (China)","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089193327","display_name":"Jianping Yin","orcid":"https://orcid.org/0000-0002-5474-4764"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianping Yin","raw_affiliation_strings":["National Univ. of Defense Technology (China)"],"affiliations":[{"raw_affiliation_string":"National Univ. of Defense Technology (China)","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102841027"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.02215301,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"10341","issue":null,"first_page":"103411Y","last_page":"103411Y"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.991599977016449,"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":0.991599977016449,"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":0.9059000015258789,"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/computer-science","display_name":"Computer science","score":0.8219483494758606},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.7837666273117065},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5793043971061707},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.49759915471076965},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4927535355091095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48294419050216675},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45697295665740967},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4435933530330658},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19957572221755981}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8219483494758606},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.7837666273117065},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5793043971061707},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.49759915471076965},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4927535355091095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48294419050216675},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45697295665740967},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4435933530330658},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19957572221755981},{"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:10.1117/12.2268406","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2268406","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1123817229","https://openalex.org/W1808644423","https://openalex.org/W1981815192","https://openalex.org/W2029069120","https://openalex.org/W2035909111","https://openalex.org/W2036640646","https://openalex.org/W2076874848","https://openalex.org/W2077844776","https://openalex.org/W2107014760","https://openalex.org/W2144073719","https://openalex.org/W2174023915","https://openalex.org/W2268272600","https://openalex.org/W2320571624","https://openalex.org/W6638249342","https://openalex.org/W6645801027","https://openalex.org/W6657765933","https://openalex.org/W6659507178","https://openalex.org/W6669790693","https://openalex.org/W6675757184"],"related_works":["https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W2017776670","https://openalex.org/W2952760143","https://openalex.org/W2347897961","https://openalex.org/W2979236518","https://openalex.org/W2358318464","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"In":[0,71],"an":[1,25,94],"abnormal":[2,51],"cervical":[3,50,125],"cell":[4,52],"detection":[5,53],"system":[6],"the":[7,17,40,43,74,81,87,92,112],"discriminated":[8],"abilities":[9],"of":[10,21,42,49,91],"different":[11],"features":[12,23],"are":[13,54,78],"not":[14],"same":[15],"so":[16],"optimized":[18],"combination":[19],"method":[20,100,107],"all":[22],"is":[24,101],"essential":[26],"component":[27],"to":[28,80,86],"this":[29,72,104],"system.":[30],"Feature":[31],"selection":[32,99],"can":[33],"improve":[34],"each":[35],"feature":[36,59,98],"utilization":[37],"ratio":[38],"and":[39],"performance":[41],"classification":[44],"problem.":[45],"The":[46,116],"previous":[47],"efforts":[48],"mainly":[55],"focused":[56],"on":[57],"changing":[58],"space":[60],"into":[61],"a":[62,67,123],"new":[63],"one":[64],"by":[65],"using":[66],"binary":[68,75],"weight":[69,76,83],"vector.":[70],"work,":[73],"values":[77],"extended":[79],"multiple":[82],"values.":[84],"According":[85],"statistical":[88],"distribution":[89],"situation":[90],"data,":[93],"adaptive":[95],"margin-based":[96],"weighted":[97],"proposed":[102],"in":[103,122],"paper.":[105],"This":[106],"performs":[108],"best":[109],"compared":[110],"with":[111],"other":[113],"3":[114],"methods.":[115],"experimental":[117],"result":[118],"achieves":[119],"96%":[120],"accuracy":[121],"real-world":[124],"smear":[126],"image":[127],"dataset.":[128]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
