{"id":"https://openalex.org/W4295073746","doi":"https://doi.org/10.1109/embc48229.2022.9872011","title":"Bilateral Analysis Boosts the Performance of Mammography-based Deep Learning Models in Breast Cancer Risk Prediction","display_name":"Bilateral Analysis Boosts the Performance of Mammography-based Deep Learning Models in Breast Cancer Risk Prediction","publication_year":2022,"publication_date":"2022-07-11","ids":{"openalex":"https://openalex.org/W4295073746","doi":"https://doi.org/10.1109/embc48229.2022.9872011","pmid":"https://pubmed.ncbi.nlm.nih.gov/36086431"},"language":"en","primary_location":{"id":"doi:10.1109/embc48229.2022.9872011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc48229.2022.9872011","pdf_url":null,"source":{"id":"https://openalex.org/S4363607706","display_name":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5010415775","display_name":"Alaa M. Ali","orcid":"https://orcid.org/0000-0002-3285-4540"},"institutions":[{"id":"https://openalex.org/I145487455","display_name":"Cairo University","ror":"https://ror.org/03q21mh05","country_code":"EG","type":"education","lineage":["https://openalex.org/I145487455"]}],"countries":["EG"],"is_corresponding":true,"raw_author_name":"Alaa Mohamed","raw_affiliation_strings":["Cairo University,Systems and Biomedical Engineering Department","Systems and Biomedical Engineering Department, Cairo University"],"affiliations":[{"raw_affiliation_string":"Cairo University,Systems and Biomedical Engineering Department","institution_ids":["https://openalex.org/I145487455"]},{"raw_affiliation_string":"Systems and Biomedical Engineering Department, Cairo University","institution_ids":["https://openalex.org/I145487455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079573009","display_name":"Sherihan Fakhry","orcid":"https://orcid.org/0000-0002-2957-517X"},"institutions":[{"id":"https://openalex.org/I196764719","display_name":"Breast Cancer Research Foundation","ror":"https://ror.org/0348ff195","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I196764719"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sherihan Fakhry","raw_affiliation_strings":["Baheya Foundation for Early Detection and Treatment of Breast Cancer,Department of Radiology","Department of Radiology, Baheya Foundation for Early Detection and Treatment of Breast Cancer"],"affiliations":[{"raw_affiliation_string":"Baheya Foundation for Early Detection and Treatment of Breast Cancer,Department of Radiology","institution_ids":["https://openalex.org/I196764719"]},{"raw_affiliation_string":"Department of Radiology, Baheya Foundation for Early Detection and Treatment of Breast Cancer","institution_ids":["https://openalex.org/I196764719"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039571699","display_name":"Tamer Basha","orcid":"https://orcid.org/0000-0003-4431-8646"},"institutions":[{"id":"https://openalex.org/I145487455","display_name":"Cairo University","ror":"https://ror.org/03q21mh05","country_code":"EG","type":"education","lineage":["https://openalex.org/I145487455"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Tamer Basha","raw_affiliation_strings":["Cairo University,Systems and Biomedical Engineering Department","Systems and Biomedical Engineering Department, Cairo University"],"affiliations":[{"raw_affiliation_string":"Cairo University,Systems and Biomedical Engineering Department","institution_ids":["https://openalex.org/I145487455"]},{"raw_affiliation_string":"Systems and Biomedical Engineering Department, Cairo University","institution_ids":["https://openalex.org/I145487455"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5010415775"],"corresponding_institution_ids":["https://openalex.org/I145487455"],"apc_list":null,"apc_paid":null,"fwci":0.4162,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.57813931,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"2022","issue":null,"first_page":"1440","last_page":"1443"},"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/T10556","display_name":"Global Cancer Incidence and Screening","score":0.9908000230789185,"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"}},{"id":"https://openalex.org/T11361","display_name":"Digital Radiography and Breast Imaging","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/breast-cancer","display_name":"Breast cancer","score":0.6926393508911133},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6517573595046997},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6037750840187073},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.5340223908424377},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5148798227310181},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47452986240386963},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.46532461047172546},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43311840295791626},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40675127506256104},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3670334219932556},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35886967182159424},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.31283867359161377},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.21673548221588135}],"concepts":[{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.6926393508911133},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6517573595046997},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6037750840187073},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.5340223908424377},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5148798227310181},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47452986240386963},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.46532461047172546},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43311840295791626},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40675127506256104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3670334219932556},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35886967182159424},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.31283867359161377},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.21673548221588135}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001940","descriptor_name":"Breast","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001940","descriptor_name":"Breast","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001940","descriptor_name":"Breast","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008327","descriptor_name":"Mammography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008327","descriptor_name":"Mammography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008327","descriptor_name":"Mammography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc48229.2022.9872011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc48229.2022.9872011","pdf_url":null,"source":{"id":"https://openalex.org/S4363607706","display_name":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:36086431","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36086431","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Gender equality","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/5"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1540266252","https://openalex.org/W1929856797","https://openalex.org/W1977112344","https://openalex.org/W1995388182","https://openalex.org/W2037764492","https://openalex.org/W2098433299","https://openalex.org/W2099644906","https://openalex.org/W2116841457","https://openalex.org/W2142722364","https://openalex.org/W2143405692","https://openalex.org/W2155254250","https://openalex.org/W2156010365","https://openalex.org/W2165664908","https://openalex.org/W2171590421","https://openalex.org/W2309472119","https://openalex.org/W2328176404","https://openalex.org/W2370924594","https://openalex.org/W2408241409","https://openalex.org/W2470394683","https://openalex.org/W2784257876","https://openalex.org/W2909714593","https://openalex.org/W2944016032","https://openalex.org/W2946085038","https://openalex.org/W2953156078","https://openalex.org/W2957629889","https://openalex.org/W2963854930","https://openalex.org/W2976378526","https://openalex.org/W2986544402","https://openalex.org/W2996116683","https://openalex.org/W3014080415","https://openalex.org/W3020578014","https://openalex.org/W3039622930","https://openalex.org/W3040996782","https://openalex.org/W3080427797","https://openalex.org/W6720898849"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W4231274751","https://openalex.org/W1549363203","https://openalex.org/W2154063878","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W1538046993","https://openalex.org/W4239293476"],"abstract_inverted_index":{"Breast":[0,23],"cancer":[1,16],"is":[2,69],"one":[3],"of":[4,8,14,72,79,98,113,127,150],"the":[5,20,40,50,70,89,95,99,111,118,157,184,197],"leading":[6],"causes":[7],"death":[9],"among":[10],"women.":[11],"Early":[12],"prediction":[13,62],"breast":[15],"can":[17,35,194],"significantly":[18,195],"improve":[19,49,60,196],"survival":[21],"rates.":[22],"density":[24],"was":[25],"proven":[26],"as":[27],"a":[28,83],"reliable":[29],"risk":[30,51,61,198],"factor.":[31],"Deep":[32],"learning":[33],"models":[34,44,63,169],"learn":[36],"subtle":[37],"cues":[38],"in":[39,53],"mammogram":[41],"images.":[42],"CNN":[43,121,158],"were":[45,160],"recently":[46],"shown":[47],"to":[48,59,76,87,186],"discrimination":[52],"full-field":[54],"mammograms.":[55],"This":[56],"study":[57],"aims":[58],"using":[64,173],"bilateral":[65,90,192],"analysis.":[66],"Bilateral":[67],"analysis":[68,193],"process":[71],"comparing":[73],"two":[74,96,171],"breasts":[75],"verify":[77],"presence":[78],"anomalies.":[80],"We":[81,102,166],"developed":[82],"Siamese":[84,115,136],"neural":[85],"network":[86],"leverage":[88],"information":[91],"and":[92,109,129,144,176],"asymmetries":[93],"between":[94],"mammograms":[97],"same":[100],"patient.":[101],"tested":[103],"our":[104,114],"model":[105,116,137],"on":[106],"271":[107],"patients":[108],"compared":[110],"results":[112,124,189],"against":[117],"traditional":[119],"unilateral":[120],"model.":[122],"Our":[123],"showed":[125],"AUCs":[126],"0.75":[128],"0.70":[130],"respectively":[131],"(p":[132],"=":[133],"0.0056).":[134],"The":[135,180,188],"also":[138],"exhibits":[139],"higher":[140],"sensitivity,":[141],"specificity,":[142],"precision,":[143],"false":[145],"positive":[146],"rate":[147],"with":[148],"values":[149,159],"0.68,":[151],"0.69,":[152],"0.71,":[153],"0.31":[154],"respectively.":[155,165],"While":[156],"0.61,":[161],"0.66,":[162],"0.67,":[163],"0.34":[164],"merged":[167],"both":[168],"by":[170],"techniques":[172],"pre-trained":[174],"weights":[175],"weighted":[177],"voting":[178],"ensemble.":[179],"merging":[181],"technique":[182],"boosted":[183],"AUC":[185],"0.78.":[187],"suggest":[190],"that":[191],"discrimination.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}