{"id":"https://openalex.org/W4412895201","doi":"https://doi.org/10.1007/s44163-025-00426-2","title":"Advanced deep learning architectures for enhanced mammography classification: a comparative study of CNNs and ViT","display_name":"Advanced deep learning architectures for enhanced mammography classification: a comparative study of CNNs and ViT","publication_year":2025,"publication_date":"2025-07-29","ids":{"openalex":"https://openalex.org/W4412895201","doi":"https://doi.org/10.1007/s44163-025-00426-2"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-025-00426-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00426-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00426-2.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00426-2.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048392616","display_name":"Shubhi Sharma","orcid":null},"institutions":[{"id":"https://openalex.org/I5847235","display_name":"University of Petroleum and Energy Studies","ror":"https://ror.org/04q2jes40","country_code":"IN","type":"education","lineage":["https://openalex.org/I5847235"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Shubhi Sharma","raw_affiliation_strings":["School of Computer Science, UPES, Dehradun, Uttarakhand, 248007, India"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, UPES, Dehradun, Uttarakhand, 248007, India","institution_ids":["https://openalex.org/I5847235"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053818694","display_name":"Yeshwant Singh","orcid":"https://orcid.org/0000-0002-4387-4002"},"institutions":[{"id":"https://openalex.org/I863896202","display_name":"Delhi Technological University","ror":"https://ror.org/01ztcvt22","country_code":"IN","type":"education","lineage":["https://openalex.org/I863896202"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Yeshwant Singh","raw_affiliation_strings":["Department of Computer Science and Engineering, Delhi Technological University, New Delhi, Delhi, 110042, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Delhi Technological University, New Delhi, Delhi, 110042, India","institution_ids":["https://openalex.org/I863896202"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021051196","display_name":"Tanupriya Choudhury","orcid":"https://orcid.org/0000-0002-9826-2759"},"institutions":[{"id":"https://openalex.org/I5847235","display_name":"University of Petroleum and Energy Studies","ror":"https://ror.org/04q2jes40","country_code":"IN","type":"education","lineage":["https://openalex.org/I5847235"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Tanupriya Choudhury","raw_affiliation_strings":["School of Computer Science, UPES, Dehradun, Uttarakhand, 248007, India"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, UPES, Dehradun, Uttarakhand, 248007, India","institution_ids":["https://openalex.org/I5847235"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048392616"],"corresponding_institution_ids":["https://openalex.org/I5847235"],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":5.2247,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.95413691,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"5","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9997000098228455,"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":0.9997000098228455,"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/T12994","display_name":"Infrared Thermography in Medicine","score":0.9925000071525574,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9905999898910522,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.5769184231758118},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5390315651893616},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.5142456889152527},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5053380131721497},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4083656966686249},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.21491339802742004},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.09499400854110718},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.059927016496658325},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.05033060908317566}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5769184231758118},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5390315651893616},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.5142456889152527},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5053380131721497},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4083656966686249},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.21491339802742004},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.09499400854110718},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.059927016496658325},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.05033060908317566}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-025-00426-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00426-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00426-2.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4610cc4e9db840069c4483c090b0df61","is_oa":true,"landing_page_url":"https://doaj.org/article/4610cc4e9db840069c4483c090b0df61","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 5, Iss 1, Pp 1-21 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-025-00426-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00426-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00426-2.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.47999998927116394}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412895201.pdf","grobid_xml":"https://content.openalex.org/works/W4412895201.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W304373761","https://openalex.org/W2148516878","https://openalex.org/W2148554069","https://openalex.org/W2149988868","https://openalex.org/W2194775991","https://openalex.org/W2328176404","https://openalex.org/W2510300688","https://openalex.org/W2533800772","https://openalex.org/W2581082771","https://openalex.org/W2592929672","https://openalex.org/W2743635406","https://openalex.org/W2908052439","https://openalex.org/W2923106228","https://openalex.org/W2962858109","https://openalex.org/W2963446712","https://openalex.org/W2975029521","https://openalex.org/W2980030301","https://openalex.org/W2998175747","https://openalex.org/W3094910079","https://openalex.org/W3113493652","https://openalex.org/W3120897110","https://openalex.org/W3126634865","https://openalex.org/W3138516171","https://openalex.org/W3163373333","https://openalex.org/W3188016109","https://openalex.org/W3195830874","https://openalex.org/W4205177272","https://openalex.org/W4206761253","https://openalex.org/W4292672344","https://openalex.org/W4296614667","https://openalex.org/W4311493227","https://openalex.org/W4312443924","https://openalex.org/W4323276171","https://openalex.org/W4361226205","https://openalex.org/W4376631151","https://openalex.org/W4385753994","https://openalex.org/W4385758936","https://openalex.org/W4387150640","https://openalex.org/W4391487214","https://openalex.org/W4392973603","https://openalex.org/W4400528496","https://openalex.org/W4405907124","https://openalex.org/W6739651123"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W3086377361"],"abstract_inverted_index":{"Breast":[0],"cancer":[1,53,192],"is":[2,16],"a":[3,27,68,171],"leading":[4],"cause":[5],"of":[6,31,110,122,164,182],"mortality":[7],"among":[8],"women":[9],"worldwide,":[10],"and":[11,44,70,88,97,107,115,129,141,154,175,185],"early":[12],"detection":[13],"via":[14,86],"mammography":[15],"critical":[17],"for":[18,51,134,161,179,190],"improving":[19],"patient":[20],"outcomes.":[21],"In":[22],"this":[23],"study,":[24],"we":[25,63],"conduct":[26],"comprehensive":[28],"comparative":[29],"analysis":[30],"15":[32],"state-of-the-art":[33],"deep":[34],"learning":[35],"models":[36,66],"including":[37],"both":[38],"general-purpose":[39],"(e.g.,":[40,47],"ResNet50,":[41],"ConvNeXt,":[42],"ViT)":[43],"mammogram-specific":[45,111],"architectures":[46,125],"FCCS-Net,":[48],"ViT-Mammo,":[49,116],"GLAM-Net)":[50],"breast":[52,191],"classification":[54],"using":[55,67],"mammographic":[56],"images.":[57],"Leveraging":[58],"four":[59],"publicly":[60],"available":[61],"datasets,":[62,151],"evaluate":[64],"all":[65],"unified":[69],"reproducible":[71],"pipeline":[72],"under":[73],"standardized":[74],"training":[75],"protocols.":[76],"Beyond":[77],"traditional":[78],"performance":[79],"metrics,":[80],"our":[81],"multi-dimensional":[82],"assessment":[83],"includes":[84],"interpretability":[85,109],"Grad-CAM":[87],"attention":[89],"maps,":[90],"calibration":[91,152],"reliability,":[92,153],"inference":[93],"time,":[94],"model":[95,148],"complexity,":[96],"deployment":[98,136,156],"feasibility.":[99],"Our":[100],"findings":[101],"highlight":[102],"the":[103,177,180],"superior":[104],"diagnostic":[105,166],"accuracy":[106],"visual":[108],"models,":[112],"particularly":[113],"FCCS-Net":[114],"with":[117],"ViT-Mammo":[118],"achieving":[119],"an":[120],"AUC":[121],"0.961.":[123],"Lightweight":[124],"such":[126],"as":[127],"EfficientNetB0":[128],"DenseNet121":[130],"demonstrate":[131],"strong":[132],"potential":[133],"edge":[135],"due":[137],"to":[138],"their":[139],"efficiency":[140],"competitive":[142],"accuracy.":[143],"The":[144],"study":[145],"further":[146],"explores":[147],"robustness":[149],"across":[150],"real-time":[155],"constraints,":[157],"offering":[158],"actionable":[159],"insights":[160],"clinical":[162],"integration":[163],"AI-driven":[165],"tools.":[167],"This":[168],"work":[169],"provides":[170],"valuable":[172],"benchmarking":[173],"framework":[174],"paves":[176],"way":[178],"development":[181],"interpretable,":[183],"efficient,":[184],"clinically":[186],"viable":[187],"AI":[188],"systems":[189],"screening.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}