{"id":"https://openalex.org/W3186513815","doi":"https://doi.org/10.1109/icit52682.2021.9491631","title":"Deep CNN Model based on VGG16 for Breast Cancer Classification","display_name":"Deep CNN Model based on VGG16 for Breast Cancer Classification","publication_year":2021,"publication_date":"2021-07-14","ids":{"openalex":"https://openalex.org/W3186513815","doi":"https://doi.org/10.1109/icit52682.2021.9491631","mag":"3186513815"},"language":"en","primary_location":{"id":"doi:10.1109/icit52682.2021.9491631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icit52682.2021.9491631","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Information Technology (ICIT)","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/A5102866359","display_name":"Dheeb Albashish","orcid":"https://orcid.org/0000-0001-9484-472X"},"institutions":[{"id":"https://openalex.org/I33926330","display_name":"Al-Balqa Applied University","ror":"https://ror.org/00qedmt22","country_code":"JO","type":"education","lineage":["https://openalex.org/I33926330"]}],"countries":["JO"],"is_corresponding":false,"raw_author_name":"Dheeb Albashish","raw_affiliation_strings":["Al-Balqa Applied University, Salt, Jordan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Al-Balqa Applied University, Salt, Jordan","institution_ids":["https://openalex.org/I33926330"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068696028","display_name":"Rizik Al-Sayyed","orcid":"https://orcid.org/0000-0001-7699-9074"},"institutions":[{"id":"https://openalex.org/I114972647","display_name":"University of Jordan","ror":"https://ror.org/05k89ew48","country_code":"JO","type":"education","lineage":["https://openalex.org/I114972647"]}],"countries":["JO"],"is_corresponding":false,"raw_author_name":"Rizik Al-Sayyed","raw_affiliation_strings":["The University of Jordan, King Abdullah II School for Information Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Jordan, King Abdullah II School for Information Technology","institution_ids":["https://openalex.org/I114972647"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101727458","display_name":"Azizi Abdullah","orcid":"https://orcid.org/0000-0002-7166-4416"},"institutions":[{"id":"https://openalex.org/I885383172","display_name":"National University of Malaysia","ror":"https://ror.org/00bw8d226","country_code":"MY","type":"education","lineage":["https://openalex.org/I885383172"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Azizi Abdullah","raw_affiliation_strings":["Center for Artificial Intelligent Technology Faculty of Information Science and Technology Universiti Kebangsaan Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Artificial Intelligent Technology Faculty of Information Science and Technology Universiti Kebangsaan Malaysia","institution_ids":["https://openalex.org/I885383172"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085113518","display_name":"Mohammad Hashem Ryalat","orcid":"https://orcid.org/0000-0002-8726-3406"},"institutions":[{"id":"https://openalex.org/I33926330","display_name":"Al-Balqa Applied University","ror":"https://ror.org/00qedmt22","country_code":"JO","type":"education","lineage":["https://openalex.org/I33926330"]}],"countries":["JO"],"is_corresponding":false,"raw_author_name":"Mohammad Hashem Ryalat","raw_affiliation_strings":["Al-Balqa Applied University, Salt, Jordan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Al-Balqa Applied University, Salt, Jordan","institution_ids":["https://openalex.org/I33926330"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001118684","display_name":"Nedaa Almansour","orcid":null},"institutions":[{"id":"https://openalex.org/I33926330","display_name":"Al-Balqa Applied University","ror":"https://ror.org/00qedmt22","country_code":"JO","type":"education","lineage":["https://openalex.org/I33926330"]}],"countries":["JO"],"is_corresponding":false,"raw_author_name":"Nedaa Ahmad Almansour","raw_affiliation_strings":["Al-Balqa Applied University, Salt, Jordan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Al-Balqa Applied University, Salt, Jordan","institution_ids":["https://openalex.org/I33926330"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.454,"has_fulltext":false,"cited_by_count":133,"citation_normalized_percentile":{"value":0.9892425,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"805","last_page":"810"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":1.0,"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":1.0,"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":0.9973000288009644,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9805999994277954,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8042041659355164},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7711871862411499},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7522193789482117},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7466394305229187},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7330814003944397},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.6318622827529907},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.591620922088623},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5666385293006897},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"Multiclass classification","score":0.5598085522651672},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5328721404075623},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.45274409651756287},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4345271587371826},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3556850552558899},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.2616735100746155}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8042041659355164},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7711871862411499},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7522193789482117},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7466394305229187},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7330814003944397},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.6318622827529907},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.591620922088623},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5666385293006897},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.5598085522651672},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5328721404075623},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.45274409651756287},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4345271587371826},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3556850552558899},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2616735100746155},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icit52682.2021.9491631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icit52682.2021.9491631","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Information Technology (ICIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2344480160","https://openalex.org/W2620578070","https://openalex.org/W2716665989","https://openalex.org/W2774261157","https://openalex.org/W2794888513","https://openalex.org/W2802565218","https://openalex.org/W2892961888","https://openalex.org/W2945323297","https://openalex.org/W2949306187","https://openalex.org/W2995942064","https://openalex.org/W3003199121","https://openalex.org/W3011493828","https://openalex.org/W3033951167","https://openalex.org/W3034193661","https://openalex.org/W3047083963","https://openalex.org/W3084893494","https://openalex.org/W3091738715","https://openalex.org/W3104261133","https://openalex.org/W3115407590","https://openalex.org/W3120023197","https://openalex.org/W3122131989","https://openalex.org/W3123769455","https://openalex.org/W3124608938","https://openalex.org/W3124643199","https://openalex.org/W6637373629","https://openalex.org/W6788327610","https://openalex.org/W6790205613"],"related_works":["https://openalex.org/W4376528628","https://openalex.org/W1537592868","https://openalex.org/W2470590370","https://openalex.org/W3176438653","https://openalex.org/W3207192536","https://openalex.org/W2981628807","https://openalex.org/W3012393889","https://openalex.org/W1748436461","https://openalex.org/W2002271516","https://openalex.org/W2910954186"],"abstract_inverted_index":{"Deep":[0],"learning":[1,30,94,123,184],"(DL)":[2],"technologies":[3],"are":[4,36,126,159,177],"becoming":[5],"a":[6,92],"buzzword":[7],"these":[8],"days,":[9],"especially":[10],"for":[11,45],"breast":[12],"histopathology":[13],"image":[14,26,47,135],"tasks,":[15],"such":[16],"as":[17],"diagnosing,":[18],"due":[19],"to":[20,58,64,74,109,128,179],"the":[21,37,85,114,149,156,162,166,170,174],"high":[22,55],"performance":[23],"obtained":[24],"in":[25,72],"classification.":[27],"Among":[28],"deep":[29,103],"types,":[31],"Convolutional":[32],"Neural":[33],"Networks":[34],"(CNN)":[35],"most":[38],"common":[39],"types":[40],"of":[41,68],"DL":[42],"models":[43,80,124,158,176],"utilized":[44,108],"medical":[46],"diagnosis":[48],"and":[49,61,71,140],"analysis.":[50],"However,":[51],"CNN":[52],"suffers":[53],"from":[54,113],"computation":[56],"cost":[57],"be":[59],"implemented":[60],"may":[62],"require":[63],"adapt":[65],"huge":[66],"number":[67],"parameters.":[69],"Thus,":[70],"order":[73],"address":[75],"this":[76,90],"issue;":[77],"several":[78],"pre-trained":[79],"have":[81],"been":[82],"established":[83],"with":[84,101,142],"predefined":[86],"network":[87],"architecture.":[88],"In":[89],"study,":[91],"transfer":[93],"model":[95,104],"based":[96],"on":[97,148,165],"Visual":[98],"Geometry":[99],"Group":[100],"16-layer":[102],"architecture":[105],"(VGG16)":[106],"is":[107],"extract":[110],"high-level":[111],"features":[112],"BreaKHis":[115],"benchmark":[116,152],"histopathological":[117,134],"images":[118],"dataset.":[119,168],"Then,":[120],"multiple":[121],"machine":[122,183],"(classifiers)":[125],"used":[127],"handle":[129],"different":[130],"Breast":[131],"Cancer":[132],"(BC)":[133],"classification":[136],"tasks":[137],"mainly:":[138],"binary":[139],"multiclass":[141],"eight-class":[143],"classifications.":[144],"The":[145],"experimental":[146],"results":[147,171],"public":[150],"BreakHis":[151],"dataset":[153],"demonstrate":[154],"that":[155,173],"proposed":[157,175],"better":[160],"than":[161],"previous":[163],"works":[164],"same":[167],"Besides,":[169],"show":[172],"able":[178],"outperform":[180],"recent":[181],"classical":[182],"algorithms.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":33},{"year":2024,"cited_by_count":31},{"year":2023,"cited_by_count":40},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
