{"id":"https://openalex.org/W4205405490","doi":"https://doi.org/10.31436/iiumej.v23i1.1825","title":"CLASSIFICATION MODEL FOR BREAST CANCER MAMMOGRAMS","display_name":"CLASSIFICATION MODEL FOR BREAST CANCER MAMMOGRAMS","publication_year":2022,"publication_date":"2022-01-04","ids":{"openalex":"https://openalex.org/W4205405490","doi":"https://doi.org/10.31436/iiumej.v23i1.1825"},"language":"en","primary_location":{"id":"doi:10.31436/iiumej.v23i1.1825","doi":"https://doi.org/10.31436/iiumej.v23i1.1825","is_oa":true,"landing_page_url":"https://doi.org/10.31436/iiumej.v23i1.1825","pdf_url":"https://journals.iium.edu.my/ejournal/index.php/iiumej/article/download/1825/838","source":{"id":"https://openalex.org/S2764858048","display_name":"IIUM Engineering Journal","issn_l":"1511-788X","issn":["1511-788X","2289-7860"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-b","norway-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310321503","host_organization_name":"IIUM Press, International Islamic University Malaysia","host_organization_lineage":["https://openalex.org/P4310321503","https://openalex.org/P4310321984"],"host_organization_lineage_names":["IIUM Press, International Islamic University Malaysia","International Islamic University Malaysia"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IIUM Engineering Journal","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journals.iium.edu.my/ejournal/index.php/iiumej/article/download/1825/838","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081821671","display_name":"Suzani Mohamad Samuri","orcid":"https://orcid.org/0000-0003-4651-1431","observed_orcids":["https://orcid.org/0000-0003-4651-1431"]},"institutions":[{"id":"https://openalex.org/I143923087","display_name":"Sultan Idris Education University","ror":"https://ror.org/005bjd415","country_code":"MY","type":"education","lineage":["https://openalex.org/I143923087"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Suzani Mohamad Samuri","raw_affiliation_strings":["Sultan Idris Education University"],"raw_orcid":"https://orcid.org/0000-0003-4651-1431","affiliations":[{"raw_affiliation_string":"Sultan Idris Education University","institution_ids":["https://openalex.org/I143923087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063716444","display_name":"Try Viananda Nova Megariani","orcid":"https://orcid.org/0000-0002-2533-3528","observed_orcids":["https://orcid.org/0000-0002-2533-3528"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Try Viananda Nova","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-2533-3528","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080759785","display_name":"Bahbibi Rahmatullah","orcid":"https://orcid.org/0000-0002-6920-8112","observed_orcids":["https://orcid.org/0000-0002-6920-8112"]},"institutions":[{"id":"https://openalex.org/I143923087","display_name":"Sultan Idris Education University","ror":"https://ror.org/005bjd415","country_code":"MY","type":"education","lineage":["https://openalex.org/I143923087"]},{"id":"https://openalex.org/I4210098426","display_name":"Universitas Ibn Khaldun Bogor","ror":"https://ror.org/00x014194","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210098426"]}],"countries":["ID","MY"],"is_corresponding":false,"raw_author_name":"Bahbibi Rahmatullah","raw_affiliation_strings":["Data Intelligence and Knowledge Management Special Interest Group, Faculty of Art, Computing and Creative Industry, Sultan Idris Education University, Malaysia","Department of Computing, Faculty of Art, Computing and Creative Industry, Sultan Idris Education University, Malaysia","Department of Informatic, Universitas Ibn Kaldun Bogor, Jawa Barat, Indonesia"],"raw_orcid":"https://orcid.org/0000-0002-6920-8112","affiliations":[{"raw_affiliation_string":"Data Intelligence and Knowledge Management Special Interest Group, Faculty of Art, Computing and Creative Industry, Sultan Idris Education University, Malaysia","institution_ids":["https://openalex.org/I143923087"]},{"raw_affiliation_string":"Department of Computing, Faculty of Art, Computing and Creative Industry, Sultan Idris Education University, Malaysia","institution_ids":["https://openalex.org/I143923087"]},{"raw_affiliation_string":"Department of Informatic, Universitas Ibn Kaldun Bogor, Jawa Barat, Indonesia","institution_ids":["https://openalex.org/I4210098426"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059367213","display_name":"Shir Li Wang","orcid":"https://orcid.org/0000-0003-4417-3213","observed_orcids":["https://orcid.org/0000-0003-4417-3213"]},"institutions":[{"id":"https://openalex.org/I143923087","display_name":"Sultan Idris Education University","ror":"https://ror.org/005bjd415","country_code":"MY","type":"education","lineage":["https://openalex.org/I143923087"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Shir Li Wang","raw_affiliation_strings":["Department of Computing, Faculty of Art, Computing and Creative Industry, Sultan Idris Education University, Malaysia"],"raw_orcid":"https://orcid.org/0000-0003-4417-3213","affiliations":[{"raw_affiliation_string":"Department of Computing, Faculty of Art, Computing and Creative Industry, Sultan Idris Education University, Malaysia","institution_ids":["https://openalex.org/I143923087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018197928","display_name":"Z.T. Al-Qaysi","orcid":"https://orcid.org/0000-0003-3595-2709","observed_orcids":["https://orcid.org/0000-0003-3595-2709"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Z.T Al-Qaysi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":140,"currency":"USD","value_usd":140},"apc_paid":{"value":140,"currency":"USD","value_usd":140},"fwci":1.3893,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.81609774,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"23","issue":"1","first_page":"187","last_page":"199"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9937000274658203,"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":0.9937000274658203,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.002300000051036477,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.002300000051036477,"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/breast-cancer","display_name":"breast cancer","score":0.8700000047683716},{"id":"https://openalex.org/keywords/mammography","display_name":"mammography","score":0.6370000243186951},{"id":"https://openalex.org/keywords/early-detection","display_name":"early detection","score":0.8529999852180481},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.7860000133514404},{"id":"https://openalex.org/keywords/naive-bayes","display_name":"naive Bayes","score":0.9210000038146973},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.9639999866485596},{"id":"https://openalex.org/keywords/gray-level-co-occurrence-matrix","display_name":"gray level co-occurrence matrix","score":0.9729999899864197},{"id":"https://openalex.org/keywords/texture-features","display_name":"texture features","score":0.9020000100135803},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"feature extraction","score":0.6019999980926514},{"id":"https://openalex.org/keywords/classification","display_name":"classification","score":0.33799999952316284},{"id":"https://openalex.org/keywords/digital-mammography","display_name":"digital mammography","score":0.6370000243186951},{"id":"https://openalex.org/keywords/model-comparison","display_name":"model comparison","score":0.5580000281333923},{"id":"https://openalex.org/keywords/kurtosis","display_name":"kurtosis","score":0.6299999952316284},{"id":"https://openalex.org/keywords/contrast","display_name":"contrast","score":0.7870000004768372},{"id":"https://openalex.org/keywords/smoothness","display_name":"smoothness","score":0.7960000038146973},{"id":"https://openalex.org/keywords/variance","display_name":"variance","score":0.8659999966621399},{"id":"https://openalex.org/keywords/standard-deviation","display_name":"standard deviation","score":0.6499999761581421},{"id":"https://openalex.org/keywords/medical-image-analysis","display_name":"medical image analysis","score":0.4429999887943268},{"id":"https://openalex.org/keywords/computer-aided-diagnosis","display_name":"computer-aided diagnosis","score":0.6579999923706055}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7493765950202942},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.743701159954071},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6269203424453735},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.5330387949943542},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4555245339870453},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45503944158554077},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45247119665145874},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3243509829044342},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.14703747630119324},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.13981735706329346},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.31436/iiumej.v23i1.1825","doi":"https://doi.org/10.31436/iiumej.v23i1.1825","is_oa":true,"landing_page_url":"https://doi.org/10.31436/iiumej.v23i1.1825","pdf_url":"https://journals.iium.edu.my/ejournal/index.php/iiumej/article/download/1825/838","source":{"id":"https://openalex.org/S2764858048","display_name":"IIUM Engineering Journal","issn_l":"1511-788X","issn":["1511-788X","2289-7860"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-b","norway-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310321503","host_organization_name":"IIUM Press, International Islamic University Malaysia","host_organization_lineage":["https://openalex.org/P4310321503","https://openalex.org/P4310321984"],"host_organization_lineage_names":["IIUM Press, International Islamic University Malaysia","International Islamic University Malaysia"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IIUM Engineering Journal","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9aaf67fdcebe467899395c794cbc0bfd","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/9aaf67fdcebe467899395c794cbc0bfd","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Islamic University Malaysia Engineering Journal, Vol 23, Iss 1 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.31436/iiumej.v23i1.1825","doi":"https://doi.org/10.31436/iiumej.v23i1.1825","is_oa":true,"landing_page_url":"https://doi.org/10.31436/iiumej.v23i1.1825","pdf_url":"https://journals.iium.edu.my/ejournal/index.php/iiumej/article/download/1825/838","source":{"id":"https://openalex.org/S2764858048","display_name":"IIUM Engineering Journal","issn_l":"1511-788X","issn":["1511-788X","2289-7860"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-b","norway-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310321503","host_organization_name":"IIUM Press, International Islamic University Malaysia","host_organization_lineage":["https://openalex.org/P4310321503","https://openalex.org/P4310321984"],"host_organization_lineage_names":["IIUM Press, International Islamic University Malaysia","International Islamic University Malaysia"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IIUM Engineering Journal","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.9391000270843506}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320325305","display_name":"Universiti Pendidikan Sultan Idris","ror":"https://ror.org/005bjd415"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4205405490.pdf","grobid_xml":"https://content.openalex.org/works/W4205405490.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1592274117","https://openalex.org/W1865474016","https://openalex.org/W1976526581","https://openalex.org/W2045256553","https://openalex.org/W2063483916","https://openalex.org/W2065867336","https://openalex.org/W2085788725","https://openalex.org/W2089046030","https://openalex.org/W2107309064","https://openalex.org/W2116825089","https://openalex.org/W2162259428","https://openalex.org/W2229512561","https://openalex.org/W2569219946","https://openalex.org/W2773381949","https://openalex.org/W2794622599","https://openalex.org/W2898197178","https://openalex.org/W2945819472","https://openalex.org/W2974726644","https://openalex.org/W2987228453","https://openalex.org/W3035655244","https://openalex.org/W3037553553","https://openalex.org/W4285088909","https://openalex.org/W4381304672"],"related_works":["https://openalex.org/W4311317157","https://openalex.org/W4232355905","https://openalex.org/W4236304939","https://openalex.org/W2989864563","https://openalex.org/W6982345686","https://openalex.org/W3181168075","https://openalex.org/W2938580828","https://openalex.org/W4401607317","https://openalex.org/W4386266736","https://openalex.org/W3121108860"],"abstract_inverted_index":{"Machine":[0,49,184,293,398],"learning":[1,35],"has":[2,133,139,218],"been":[3,134,140],"the":[4,26,58,64,67,71,74,86,90,95,100,125,128,137,149,152,159,164,187,194,197,204,225,238,241,244],"topic":[5],"of":[6,14,33,73,89,108,151,154,158,196,206,240],"interest":[7],"in":[8,94,99,191,208,212,224],"research":[9],"related":[10],"to":[11,56,146],"early":[12,245],"detection":[13],"breast":[15,75,198,242],"cancer":[16],"based":[17],"on":[18],"mammogram":[19,54,299],"images.":[20],"In":[21],"this":[22],"study,":[23,226],"we":[24],"compare":[25],"performance":[27,153],"results":[28,190],"from":[29],"three":[30],"(3)":[31,276],"types":[32],"machine":[34],"techniques:":[36],"1)":[37,281],"Na\u00efve":[38,282],"Bayes":[39,283],"(NB),":[40,284],"2)":[41,285],"Neural":[42,286],"Network":[43,287],"(NN)":[44,288],"and":[45,70,115,122,136,167,210,221,227],"3)":[46,290],"Support":[47,182,291,396],"Vector":[48,183,292,397],"(SVM)":[50,185,294,399],"with":[51,203],"2000":[52,296],"digital":[53,298],"images":[55],"choose":[57],"best":[59],"technique":[60],"that":[61,230],"could":[62],"model":[63,217,223,429],"relationship":[65],"between":[66],"features":[68],"extracted":[69,121],"state":[72,195,239],"(\u2018Normal\u2019":[76],"or":[77,201],"\u2018Cancer\u2019).":[78],"Grey":[79,319],"Level":[80,320],"Co-occurrence":[81,321],"Matrix":[82,322],"(GLCM)":[83,323],"which":[84],"represents":[85],"two":[87],"dimensions":[88],"level":[91],"variation":[92],"gray":[93],"image":[96],"is":[97,232],"used":[98,123,162,170],"feature":[101,120],"extraction":[102],"process.":[103,130],"Six":[104],"(6)":[105,339],"attributes":[106],"consist":[107],"contrast,":[109],"variance,":[110],"standard":[111],"deviation,":[112],"kurtosis,":[113,347],"mean":[114],"smoothness":[116],"were":[117,161],"computed":[118],"as":[119,124,163,171,199],"inputs":[126],"for":[127,142,148,236],"classification":[129,216],"The":[131,174,214],"data":[132,160,166,377,380,387],"randomized":[135],"experiment":[138],"repeated":[141],"ten":[143,177],"(10)":[144,178,368,392],"times":[145],"check":[147],"consistencies":[150],"all":[155],"techniques.":[156],"70%":[157,376],"training":[165,209],"another":[168],"30%":[169,383],"testing":[172],"data.":[173],"result":[175],"after":[176],"experiments":[179],"show":[180],"that,":[181],"gives":[186],"most":[188],"consistent":[189],"correctly":[192],"classifying":[193],"\u2018Normal\u2019":[200],"\u2018Cancer\u2019,":[202],"accuracy":[205],"99.4%,":[207,417],"98.76%":[211,421],"testing.":[213],"SVM":[215,231,426,440],"outperformed":[219],"NN":[220,430],"NB":[222,432],"it":[228],"shows":[229],"a":[233],"good":[234],"choice":[235],"determining":[237],"at":[243],"stage.":[246],"ABSTRAK:":[247],"Pembelajaran":[248],"mesin":[249],"telah":[250,364,427],"menjadi":[251],"topik":[252],"yang":[253,257,303,309,324,354,402,443],"diminati":[254],"dalam":[255,334,405,418,422,433],"penyelidikan":[256],"berkaitan":[258],"dengan":[259,295,409,415],"pengesanan":[260],"awal":[261],"kanser":[262],"payudara":[263,313,408,448],"berdasarkan":[264],"imej":[265,297],"mamogram.":[266],"Dalam":[267],"kajian":[268,434],"ini,":[269,435],"kami":[270],"membandingkan":[271],"hasil":[272,401],"prestasi":[273,373],"dari":[274,342],"tiga":[275],"jenis":[277],"teknik":[278,301],"pembelajaran":[279],"mesin:":[280],"dan":[289,311,349,356,382,420,431,436],"hingga":[300],"terbaik":[302],"dapat":[304,317],"memodelkan":[305],"hubungan":[306],"antara":[307],"ciri":[308],"diekstraksi":[310],"keadaan":[312,407,447],"('Normal'":[314],"atau":[315,413],"'Cancer')":[316],"diperoleh.":[318],"mewakili":[325],"dua":[326],"dimensi":[327],"variasi":[328],"tahap":[329],"kelabu":[330],"pada":[331,449],"gambar":[332],"digunakan":[333,357,378,385],"proses":[335,361],"pengekstrakan":[336],"ciri.":[337],"Enam":[338],"atribut":[340],"terdiri":[341],"kontras,":[343],"varians,":[344],"sisihan":[345],"piawai,":[346],"min":[348],"kehalusan":[350],"dihitung":[351],"sebagai":[352,358,379,386,411],"fitur":[353],"diekstrak":[355],"input":[359],"untuk":[360,370,445],"klasifikasi.":[362],"Eksperimen":[363],"diulang":[365],"selama":[366],"sepuluh":[367,391],"kali":[369],"memeriksa":[371],"kesesuaian":[372],"semua":[374],"teknik.":[375],"latihan":[381,419],"lagi":[384],"ujian.":[388,423],"Hasil":[389],"setelah":[390],"eksperimen":[393],"menunjukkan":[394,438],"bahawa,":[395],"memberikan":[400],"paling":[403],"konsisten":[404],"mengklasifikasikan":[406],"betul":[410],"'Normal'":[412],"'Kanser',":[414],"akurasi":[416],"Model":[424],"klasifikasi":[425],"mengungguli":[428],"ia":[437],"bahawa":[439],"adalah":[441],"pilihan":[442],"baik":[444],"menentukan":[446],"peringkat":[450],"awal.":[451]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2022-01-25T00:00:00"}
