{"id":"https://openalex.org/W4400908857","doi":"https://doi.org/10.1109/siu61531.2024.10601012","title":"Deep Learning Approach to Improve Breast CancerClassification for Screening Mammography","display_name":"Deep Learning Approach to Improve Breast CancerClassification for Screening Mammography","publication_year":2024,"publication_date":"2024-05-15","ids":{"openalex":"https://openalex.org/W4400908857","doi":"https://doi.org/10.1109/siu61531.2024.10601012"},"language":"en","primary_location":{"id":"doi:10.1109/siu61531.2024.10601012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu61531.2024.10601012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 32nd Signal Processing and Communications Applications Conference (SIU)","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/A5111265734","display_name":"Fatemah Faraji","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Fatemah Faraji","raw_affiliation_strings":["Bilgisayar Mühendisliği Bölümü Yıldız Teknik Üniversitesi,İstanbul,Türkiye,34220"],"affiliations":[{"raw_affiliation_string":"Bilgisayar Mühendisliği Bölümü Yıldız Teknik Üniversitesi,İstanbul,Türkiye,34220","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082045666","display_name":"G\u00f6khan Bilgin","orcid":"https://orcid.org/0000-0002-5532-477X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gokhan Bilgin","raw_affiliation_strings":["Bilgisayar Mühendisliği Bölümü Yıldız Teknik Üniversitesi,İstanbul,Türkiye,34220"],"affiliations":[{"raw_affiliation_string":"Bilgisayar Mühendisliği Bölümü Yıldız Teknik Üniversitesi,İstanbul,Türkiye,34220","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5111265734"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0911,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.80674326,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.995199978351593,"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":0.995199978351593,"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":0.9193999767303467,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.7575782537460327},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6298726797103882},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.483381450176239},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4368833899497986},{"id":"https://openalex.org/keywords/mammography-screening","display_name":"Mammography screening","score":0.4260209798812866},{"id":"https://openalex.org/keywords/medical-physics","display_name":"Medical physics","score":0.37018805742263794},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32966482639312744},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.26046222448349},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.21263349056243896},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.09808787703514099},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.06325262784957886}],"concepts":[{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.7575782537460327},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6298726797103882},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.483381450176239},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4368833899497986},{"id":"https://openalex.org/C2994436140","wikidata":"https://www.wikidata.org/wiki/Q17011492","display_name":"Mammography screening","level":5,"score":0.4260209798812866},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.37018805742263794},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32966482639312744},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.26046222448349},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.21263349056243896},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.09808787703514099},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.06325262784957886}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu61531.2024.10601012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu61531.2024.10601012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 32nd Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2940901905","https://openalex.org/W2961936350","https://openalex.org/W2969326038","https://openalex.org/W2996667721","https://openalex.org/W3027335902","https://openalex.org/W3034033704","https://openalex.org/W3111749256","https://openalex.org/W3131500599","https://openalex.org/W3138516171","https://openalex.org/W3184144206","https://openalex.org/W4200467578","https://openalex.org/W4214913449","https://openalex.org/W4296018857","https://openalex.org/W4308119975","https://openalex.org/W6779863994"],"related_works":["https://openalex.org/W4380075502","https://openalex.org/W2025749204","https://openalex.org/W2012889557","https://openalex.org/W2410332468","https://openalex.org/W2025948621","https://openalex.org/W4302763194","https://openalex.org/W3123882489","https://openalex.org/W658877851","https://openalex.org/W1984382920","https://openalex.org/W2093759824"],"abstract_inverted_index":{"Identifying":[0],"breast":[1,4,15,114],"masses":[2,27,77],"in":[3,10,28,62,71,84],"cancer":[5,16,115],"is":[6],"a":[7,35,55,94],"crucial":[8],"step":[9],"the":[11,20,29,41,63,68,89,109],"early":[12],"diagnosis":[13],"of":[14,32,91,97,113],"through":[17,117],"mammography.":[18],"However,":[19],"differential":[21],"features":[22],"between":[23,73],"benign":[24,74],"and":[25,75,111],"cancerous":[26],"initial":[30],"stages":[31],"detection":[33,116],"pose":[34],"persistent":[36],"challenge.":[37],"In":[38],"response":[39],"to":[40,66,103,107],"limitations":[42],"faced":[43],"by":[44,78],"traditional":[45],"convolutional":[46],"neural":[47],"networks,":[48],"vision":[49,98],"transformers":[50],"are":[51],"gaining":[52],"importance":[53],"as":[54],"promising":[56],"approach.":[57],"The":[58],"transducer-based":[59],"approach":[60],"used":[61],"study":[64],"aims":[65],"overcome":[67],"inherent":[69],"difficulties":[70],"distinguishing":[72],"malignant":[76],"offering":[79],"improved":[80],"or":[81],"comparable":[82],"performance":[83],"classifying":[85],"natural":[86],"images.":[87],"Within":[88],"framework":[90],"this":[92],"study,":[93],"comprehensive":[95],"comparison":[96],"transducer":[99],"models":[100],"was":[101],"conducted":[102],"examine":[104],"their":[105],"potential":[106],"increase":[108],"accuracy":[110],"efficiency":[112],"mammography":[118],"imaging.":[119]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}