{"id":"https://openalex.org/W4322504029","doi":"https://doi.org/10.1108/dta-08-2022-0330","title":"Binary classification of multi-magnification histopathological breast cancer images using late fusion and transfer learning","display_name":"Binary classification of multi-magnification histopathological breast cancer images using late fusion and transfer learning","publication_year":2023,"publication_date":"2023-02-27","ids":{"openalex":"https://openalex.org/W4322504029","doi":"https://doi.org/10.1108/dta-08-2022-0330"},"language":"en","primary_location":{"id":"doi:10.1108/dta-08-2022-0330","is_oa":false,"landing_page_url":"https://doi.org/10.1108/dta-08-2022-0330","pdf_url":null,"source":{"id":"https://openalex.org/S4210171756","display_name":"Data Technologies and Applications","issn_l":"2514-9288","issn":["2514-9288","2514-9318"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Technologies and Applications","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/A5025339815","display_name":"Fatima-Zahrae Nakach","orcid":"https://orcid.org/0000-0002-8465-5041"},"institutions":[{"id":"https://openalex.org/I4210131560","display_name":"Universit\u00e9 Mohammed VI Polytechnique","ror":"https://ror.org/03xc55g68","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210131560"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Fatima-Zahrae Nakach","raw_affiliation_strings":["Modeling, Simulation and Data Analysis, Mohammed VI Polytechnic University, Ben Guerir, Morocco"],"raw_orcid":"https://orcid.org/0000-0002-8465-5041","affiliations":[{"raw_affiliation_string":"Modeling, Simulation and Data Analysis, Mohammed VI Polytechnic University, Ben Guerir, Morocco","institution_ids":["https://openalex.org/I4210131560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012997021","display_name":"Hasnae Zerouaoui","orcid":"https://orcid.org/0000-0001-7268-8404"},"institutions":[{"id":"https://openalex.org/I4210131560","display_name":"Universit\u00e9 Mohammed VI Polytechnique","ror":"https://ror.org/03xc55g68","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210131560"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Hasnae Zerouaoui","raw_affiliation_strings":["Modeling, Simulation and Data Analysis, Mohammed VI Polytechnic University, Ben Guerir, Morocco"],"raw_orcid":"https://orcid.org/0000-0001-7268-8404","affiliations":[{"raw_affiliation_string":"Modeling, Simulation and Data Analysis, Mohammed VI Polytechnic University, Ben Guerir, Morocco","institution_ids":["https://openalex.org/I4210131560"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000218612","display_name":"Ali Idri","orcid":"https://orcid.org/0000-0002-4586-4158"},"institutions":[{"id":"https://openalex.org/I4210131560","display_name":"Universit\u00e9 Mohammed VI Polytechnique","ror":"https://ror.org/03xc55g68","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210131560"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Ali Idri","raw_affiliation_strings":["Modeling, Simulation and Data Analysis, Mohammed VI Polytechnic University, Ben Guerir, Morocco"],"raw_orcid":"https://orcid.org/0000-0002-4586-4158","affiliations":[{"raw_affiliation_string":"Modeling, Simulation and Data Analysis, Mohammed VI Polytechnic University, Ben Guerir, Morocco","institution_ids":["https://openalex.org/I4210131560"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210131560"],"apc_list":null,"apc_paid":null,"fwci":0.6452,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.73308677,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"57","issue":"5","first_page":"668","last_page":"695"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9991999864578247,"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/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/magnification","display_name":"Magnification","score":0.8224858045578003},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7105890512466431},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5816066265106201},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.569847047328949},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5564556121826172},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.5217986106872559},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.4187219738960266},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34594160318374634},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.31117191910743713},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.27170586585998535},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.20863518118858337},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.07785594463348389}],"concepts":[{"id":"https://openalex.org/C4144372","wikidata":"https://www.wikidata.org/wiki/Q675287","display_name":"Magnification","level":2,"score":0.8224858045578003},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7105890512466431},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5816066265106201},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.569847047328949},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5564556121826172},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.5217986106872559},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.4187219738960266},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34594160318374634},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.31117191910743713},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.27170586585998535},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.20863518118858337},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.07785594463348389}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/dta-08-2022-0330","is_oa":false,"landing_page_url":"https://doi.org/10.1108/dta-08-2022-0330","pdf_url":null,"source":{"id":"https://openalex.org/S4210171756","display_name":"Data Technologies and Applications","issn_l":"2514-9288","issn":["2514-9288","2514-9318"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Technologies and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W22229905","https://openalex.org/W861925310","https://openalex.org/W1502609557","https://openalex.org/W2030623877","https://openalex.org/W2071698610","https://openalex.org/W2098613164","https://openalex.org/W2103522741","https://openalex.org/W2113622720","https://openalex.org/W2133114940","https://openalex.org/W2149684865","https://openalex.org/W2165698076","https://openalex.org/W2295797531","https://openalex.org/W2344480160","https://openalex.org/W2602516395","https://openalex.org/W2607306668","https://openalex.org/W2609584387","https://openalex.org/W2619383789","https://openalex.org/W2658641687","https://openalex.org/W2716665989","https://openalex.org/W2737813497","https://openalex.org/W2767290858","https://openalex.org/W2767410506","https://openalex.org/W2792433889","https://openalex.org/W2796438033","https://openalex.org/W2800002784","https://openalex.org/W2801540580","https://openalex.org/W2806794512","https://openalex.org/W2882981877","https://openalex.org/W2899429952","https://openalex.org/W2901645117","https://openalex.org/W2904184790","https://openalex.org/W2907760128","https://openalex.org/W2945819472","https://openalex.org/W2954229473","https://openalex.org/W2954996726","https://openalex.org/W2977153525","https://openalex.org/W2978760586","https://openalex.org/W2982406227","https://openalex.org/W2991603289","https://openalex.org/W2998584127","https://openalex.org/W2999309192","https://openalex.org/W3003199121","https://openalex.org/W3006138035","https://openalex.org/W3009268531","https://openalex.org/W3031941587","https://openalex.org/W3090140268","https://openalex.org/W3094595351","https://openalex.org/W3119441468","https://openalex.org/W3120006163","https://openalex.org/W3126442124","https://openalex.org/W3131021614","https://openalex.org/W3159213628","https://openalex.org/W3182164228","https://openalex.org/W3199776813","https://openalex.org/W3201054345","https://openalex.org/W3215071662","https://openalex.org/W4212883601","https://openalex.org/W4214594467","https://openalex.org/W4280497490","https://openalex.org/W4281821782","https://openalex.org/W4285412802","https://openalex.org/W4309484525","https://openalex.org/W6793364036"],"related_works":["https://openalex.org/W2041117173","https://openalex.org/W4256609757","https://openalex.org/W2152595177","https://openalex.org/W1810141276","https://openalex.org/W2005715326","https://openalex.org/W2418534670","https://openalex.org/W2022127494","https://openalex.org/W2047186806","https://openalex.org/W2171082272","https://openalex.org/W2023135624"],"abstract_inverted_index":{"Purpose":[0],"Histopathology":[1],"biopsy":[2],"imaging":[3],"is":[4,36],"currently":[5],"the":[6,10,20,27,40,49,69,97,102,116,119,144,154,160,165,171,180],"gold":[7],"standard":[8],"for":[9,68,188],"diagnosis":[11],"of":[12,29,51,72,101,118,153,182,224,229,234,241],"breast":[13,73,93,190],"cancer":[14,191],"in":[15],"clinical":[16],"practice.":[17],"Pathologists":[18],"examine":[19],"images":[21,95],"at":[22],"various":[23],"magnifications":[24],"to":[25,57,91,147],"identify":[26],"type":[28],"tumor":[30,74,94],"because":[31,198],"if":[32],"only":[33],"one":[34],"magnification":[35,99,124,207],"taken":[37],"into":[38],"account,":[39],"decision":[41],"may":[42],"not":[43],"be":[44],"accurate.":[45],"This":[46,177],"study":[47,178],"explores":[48],"performance":[50],"transfer":[52,183],"learning":[53,66,80,184],"and":[54,86,112,133,143,164,185,218,238],"late":[55,186],"fusion":[56,187],"construct":[58],"multi-scale":[59,212],"ensembles":[60,197,213],"that":[61],"fuse":[62,115],"different":[63,123,126],"magnification-specific":[64],"deep":[65,79],"models":[67,120,156,167,203,217],"binary":[70],"classification":[71,193],"slides.":[75],"Design/methodology/approach":[76],"Three":[77],"pretrained":[78],"techniques":[81],"(DenseNet":[82],"201,":[83],"MobileNet":[84],"v2":[85],"Inception":[87],"v3)":[88],"were":[89,128,168],"used":[90],"classify":[92],"over":[96],"four":[98],"factors":[100],"Breast":[103],"Cancer":[104],"Histopathological":[105],"Image":[106],"Classification":[107],"dataset":[108],"(40\u00d7,":[109],"100\u00d7,":[110],"200\u00d7":[111],"400\u00d7).":[113],"To":[114],"predictions":[117,139],"trained":[121,136,204],"on":[122,137,205],"factors,":[125],"aggregators":[127],"used,":[129],"including":[130],"weighted":[131],"voting":[132,174],"seven":[134],"meta-classifiers":[135],"slide":[138],"using":[140,159,170],"class":[141],"labels":[142],"probabilities":[145],"assigned":[146],"each":[148,206],"class.":[149],"The":[150,210],"best":[151,211],"cluster":[152],"outperforming":[155],"was":[157],"chosen":[158],"Scott\u2013Knott":[161],"statistical":[162],"test,":[163],"top":[166],"ranked":[169],"Borda":[172],"count":[173],"system.":[175],"Findings":[176],"recommends":[179],"use":[181],"histopathological":[189],"image":[192],"by":[194],"constructing":[195],"multi-magnification":[196],"they":[199],"perform":[200],"better":[201],"than":[202],"separately.":[208],"Originality/value":[209],"outperformed":[214],"state-of-the-art":[215],"integrated":[216],"achieved":[219],"an":[220],"accuracy":[221],"mean":[222],"value":[223],"98.82":[225],"per":[226,231,236,243],"cent,":[227,232],"precision":[228],"98.46":[230],"recall":[233],"100":[235],"cent":[237],"F":[239],"1-score":[240],"99.20":[242],"cent.":[244]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
