{"id":"https://openalex.org/W2605260836","doi":"https://doi.org/10.3233/fi-2017-1487","title":"Abnormal Breast Detection in Mammogram Images by Feed-forward Neural Network Trained by Jaya Algorithm","display_name":"Abnormal Breast Detection in Mammogram Images by Feed-forward Neural Network Trained by Jaya Algorithm","publication_year":2017,"publication_date":"2017-03-11","ids":{"openalex":"https://openalex.org/W2605260836","doi":"https://doi.org/10.3233/fi-2017-1487","mag":"2605260836"},"language":"en","primary_location":{"id":"doi:10.3233/fi-2017-1487","is_oa":false,"landing_page_url":"https://doi.org/10.3233/fi-2017-1487","pdf_url":null,"source":{"id":"https://openalex.org/S39012697","display_name":"Fundamenta Informaticae","issn_l":"0169-2968","issn":["0169-2968","1875-8681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fundamenta Informaticae","raw_type":"journal-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/A5007987858","display_name":"Shuihua Wang\u200e","orcid":"https://orcid.org/0000-0003-4713-2791"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuihua Wang","raw_affiliation_strings":["School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu 210023, China. wangshuihua@njnu.edu.cn"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu 210023, China. wangshuihua@njnu.edu.cn","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069123141","display_name":"R. Venkata Rao","orcid":"https://orcid.org/0000-0002-9957-1086"},"institutions":[{"id":"https://openalex.org/I42014448","display_name":"Sardar Vallabhbhai National Institute of Technology Surat","ror":"https://ror.org/02y394t43","country_code":"IN","type":"education","lineage":["https://openalex.org/I42014448"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ravipudi Venkata Rao","raw_affiliation_strings":["Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Ichchanath, Surat-395 007, Gujarat State, India"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Ichchanath, Surat-395 007, Gujarat State, India","institution_ids":["https://openalex.org/I42014448"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025643309","display_name":"Peng Chen","orcid":"https://orcid.org/0000-0002-1669-0013"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peng Chen","raw_affiliation_strings":["Department of Electrical Engineering, Columbia University, New York, NY 10027, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Columbia University, New York, NY 10027, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100434437","display_name":"Yudong Zhang","orcid":"https://orcid.org/0000-0002-4870-1493"},"institutions":[{"id":"https://openalex.org/I4210144799","display_name":"Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing","ror":"https://ror.org/04dzj3g56","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210144799"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yudong Zhang","raw_affiliation_strings":["Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu 210042, China. zhangyudong@njnu.edu.cn"],"affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu 210042, China. zhangyudong@njnu.edu.cn","institution_ids":["https://openalex.org/I4210144799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100626353","display_name":"Aijun Liu","orcid":"https://orcid.org/0000-0001-7235-9424"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aijun Liu","raw_affiliation_strings":["W.P. Carey School of Business, Arizona State University, Tempe, AZ 85287, USA"],"affiliations":[{"raw_affiliation_string":"W.P. Carey School of Business, Arizona State University, Tempe, AZ 85287, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018462307","display_name":"Ling Wei","orcid":"https://orcid.org/0000-0002-9086-4368"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Wei","raw_affiliation_strings":["School of Electronic Information & Electrical Engineering, Shanghai Jiaotong University, Shanghai 200030, China","Journal:"],"affiliations":[{"raw_affiliation_string":"School of Electronic Information & Electrical Engineering, Shanghai Jiaotong University, Shanghai 200030, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Journal:","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100434437"],"corresponding_institution_ids":["https://openalex.org/I4210144799"],"apc_list":null,"apc_paid":null,"fwci":5.6433,"has_fulltext":false,"cited_by_count":109,"citation_normalized_percentile":{"value":0.97559796,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"151","issue":"1-4","first_page":"191","last_page":"211"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.998199999332428,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.998199999332428,"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"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9944000244140625,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9897000193595886,"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/principal-component-analysis","display_name":"Principal component analysis","score":0.709278404712677},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6706506013870239},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6221897006034851},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.5985566973686218},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5820066928863525},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5777068734169006},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5452760457992554},{"id":"https://openalex.org/keywords/cad","display_name":"CAD","score":0.4748035967350006},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45411044359207153},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.10840320587158203},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.09860798716545105},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08335745334625244}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.709278404712677},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6706506013870239},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6221897006034851},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.5985566973686218},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5820066928863525},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5777068734169006},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5452760457992554},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.4748035967350006},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45411044359207153},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.10840320587158203},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.09860798716545105},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08335745334625244},{"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/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/fi-2017-1487","is_oa":false,"landing_page_url":"https://doi.org/10.3233/fi-2017-1487","pdf_url":null,"source":{"id":"https://openalex.org/S39012697","display_name":"Fundamenta Informaticae","issn_l":"0169-2968","issn":["0169-2968","1875-8681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fundamenta Informaticae","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","display_name":"Gender equality","score":0.6299999952316284}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W916788948","https://openalex.org/W1158817551","https://openalex.org/W1672221038","https://openalex.org/W1698059316","https://openalex.org/W1904440782","https://openalex.org/W1933512202","https://openalex.org/W1963939054","https://openalex.org/W1964023755","https://openalex.org/W1970761865","https://openalex.org/W1971167497","https://openalex.org/W1979894926","https://openalex.org/W1986140989","https://openalex.org/W1988280900","https://openalex.org/W1990645316","https://openalex.org/W1999140879","https://openalex.org/W1999284878","https://openalex.org/W2008987006","https://openalex.org/W2009964255","https://openalex.org/W2018720693","https://openalex.org/W2021655555","https://openalex.org/W2023179925","https://openalex.org/W2025208635","https://openalex.org/W2026004691","https://openalex.org/W2035199208","https://openalex.org/W2041642242","https://openalex.org/W2044699402","https://openalex.org/W2050729568","https://openalex.org/W2056622672","https://openalex.org/W2057451158","https://openalex.org/W2058807357","https://openalex.org/W2060117429","https://openalex.org/W2061261675","https://openalex.org/W2066650517","https://openalex.org/W2067568688","https://openalex.org/W2074091762","https://openalex.org/W2081341085","https://openalex.org/W2085177807","https://openalex.org/W2088357067","https://openalex.org/W2092709759","https://openalex.org/W2116353952","https://openalex.org/W2150575165","https://openalex.org/W2154423420","https://openalex.org/W2163445909","https://openalex.org/W2262790950","https://openalex.org/W2319846832","https://openalex.org/W2321077867","https://openalex.org/W2558107930","https://openalex.org/W3110835628"],"related_works":["https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W3205213561","https://openalex.org/W2531880140","https://openalex.org/W2334610590","https://openalex.org/W2320366403","https://openalex.org/W3204197061","https://openalex.org/W2036609560","https://openalex.org/W4251350712","https://openalex.org/W1978794434"],"abstract_inverted_index":{"(Aim)":[0],"Abnormal":[1],"breast":[2],"can":[3],"be":[4],"diagnosed":[5],"using":[6],"the":[7,39,43,53,68,84,98],"digital":[8],"mammography.":[9],"Traditional":[10],"manual":[11],"interpretation":[12],"method":[13],"cannot":[14],"yield":[15],"high":[16],"accuracy.":[17],"(Method)":[18],"In":[19],"this":[20],"study,":[21],"we":[22,37],"proposed":[23,102,127],"a":[24,87],"novel":[25,88],"computer-aided":[26],"diagnosis":[27],"system":[28,129],"for":[29],"detecting":[30,133],"abnormal":[31,134],"breasts":[32,135],"in":[33,132,148],"mammogram":[34],"images.":[35],"First,":[36],"segmented":[38],"region-o":[40],"f-interest.":[41],"Next,":[42],"weighted-type":[44],"fractional":[45],"Fourier":[46],"transform":[47],"(WFRFT)":[48],"was":[49,62,80,94],"employed":[50,95],"to":[51,66,70,82,96],"obtain":[52],"unified":[54],"time-frequency":[55],"spectrum.":[56],"Third,":[57],"principal":[58,73],"component":[59],"analysis":[60],"(PCA)":[61],"introduced":[63],"and":[64,119,136,156],"used":[65],"reduce":[67],"spectrum":[69],"only":[71],"18":[72],"components.":[74],"Fourth,":[75],"feed-forward":[76],"neural":[77],"network":[78],"(FNN)":[79],"utilized":[81],"generate":[83],"classifier.":[85,99],"Finally,":[86],"algorithm-specific":[89],"parameter":[90],"free":[91],"approach,":[92],"Jaya,":[93],"train":[97],"(Results)":[100],"Our":[101],"WFRFT":[103],"+":[104,106],"PCA":[105],"Jaya-FNN":[107],"achieved":[108],"sensitivity":[109],"of":[110,115,121],"92.26%":[111],"\u00b1":[112,117,123],"3.44%,":[113],"specificity":[114],"92.28%":[116],"3.58%,":[118],"accuracy":[120],"92.27%":[122],"3.49%.":[124],"(Conclusions)":[125],"The":[126],"CAD":[128],"is":[130,145],"effective":[131,147],"performs":[137],"better":[138],"than":[139,151],"5":[140],"state-of-the-art":[141],"systems.":[142],"Besides,":[143],"Jaya":[144],"more":[146],"training":[149],"FNN":[150],"BP,":[152],"MBP,":[153],"GA,":[154],"SA,":[155],"PSO.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":19},{"year":2018,"cited_by_count":17},{"year":2017,"cited_by_count":13}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
