{"id":"https://openalex.org/W4392362001","doi":"https://doi.org/10.1007/s10489-024-05358-5","title":"A self-supervised learning model based on variational autoencoder for limited-sample mammogram classification","display_name":"A self-supervised learning model based on variational autoencoder for limited-sample mammogram classification","publication_year":2024,"publication_date":"2024-02-01","ids":{"openalex":"https://openalex.org/W4392362001","doi":"https://doi.org/10.1007/s10489-024-05358-5"},"language":"en","primary_location":{"id":"doi:10.1007/s10489-024-05358-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-024-05358-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-024-05358-5.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10489-024-05358-5.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087674388","display_name":"Meryem Alt\u0131n Karag\u00f6z","orcid":"https://orcid.org/0000-0002-8275-5356"},"institutions":[{"id":"https://openalex.org/I12700597","display_name":"Sivas Cumhuriyet \u00dcniversitesi","ror":"https://ror.org/04f81fm77","country_code":"TR","type":"education","lineage":["https://openalex.org/I12700597"]},{"id":"https://openalex.org/I87673952","display_name":"Erciyes University","ror":"https://ror.org/047g8vk19","country_code":"TR","type":"education","lineage":["https://openalex.org/I87673952"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Meryem Altin Karagoz","raw_affiliation_strings":["Artificial Intelligence and Big Data Application and Research Center, Erciyes University, Kayseri, Turkey","Department of Computer Engineering, Erciyes University, Kayseri, Turkey","Department of Computer Engineering, Sivas Cumhuriyet University, Sivas, Turkey"],"raw_orcid":"https://orcid.org/0000-0002-8275-5356","affiliations":[{"raw_affiliation_string":"Artificial Intelligence and Big Data Application and Research Center, Erciyes University, Kayseri, Turkey","institution_ids":["https://openalex.org/I87673952"]},{"raw_affiliation_string":"Department of Computer Engineering, Erciyes University, Kayseri, Turkey","institution_ids":["https://openalex.org/I87673952"]},{"raw_affiliation_string":"Department of Computer Engineering, Sivas Cumhuriyet University, Sivas, Turkey","institution_ids":["https://openalex.org/I12700597"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027892983","display_name":"\u00d6zkan Ufuk Nalbanto\u011flu","orcid":"https://orcid.org/0000-0002-2278-7786"},"institutions":[{"id":"https://openalex.org/I87673952","display_name":"Erciyes University","ror":"https://ror.org/047g8vk19","country_code":"TR","type":"education","lineage":["https://openalex.org/I87673952"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"O. Ufuk Nalbantoglu","raw_affiliation_strings":["Artificial Intelligence and Big Data Application and Research Center, Erciyes University, Kayseri, Turkey","Department of Computer Engineering, Erciyes University, Kayseri, Turkey","Genome and Stem Cell Center (GenK\u00f6k), Erciyes University, Kayseri, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Artificial Intelligence and Big Data Application and Research Center, Erciyes University, Kayseri, Turkey","institution_ids":["https://openalex.org/I87673952"]},{"raw_affiliation_string":"Department of Computer Engineering, Erciyes University, Kayseri, Turkey","institution_ids":["https://openalex.org/I87673952"]},{"raw_affiliation_string":"Genome and Stem Cell Center (GenK\u00f6k), Erciyes University, Kayseri, Turkey","institution_ids":["https://openalex.org/I87673952"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5087674388"],"corresponding_institution_ids":["https://openalex.org/I12700597","https://openalex.org/I87673952"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":4.8619,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.95485617,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"54","issue":"4","first_page":"3448","last_page":"3463"},"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":0.9980999827384949,"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":0.9905999898910522,"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/computer-science","display_name":"Computer science","score":0.8440777063369751},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7465008497238159},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7413280010223389},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.634288489818573},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6104432344436646},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5959059596061707},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5219347476959229},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48644018173217773},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.4239284098148346},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.41873592138290405},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.26129892468452454}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8440777063369751},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7465008497238159},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7413280010223389},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.634288489818573},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6104432344436646},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5959059596061707},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5219347476959229},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48644018173217773},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.4239284098148346},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.41873592138290405},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.26129892468452454},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10489-024-05358-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-024-05358-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-024-05358-5.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10489-024-05358-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-024-05358-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-024-05358-5.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.699999988079071,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321621","display_name":"Sivas Cumhuriyet \u00dcniversitesi","ror":"https://ror.org/04f81fm77"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392362001.pdf","grobid_xml":"https://content.openalex.org/works/W4392362001.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W304373761","https://openalex.org/W1901129140","https://openalex.org/W2010351317","https://openalex.org/W2100495367","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2321533354","https://openalex.org/W2326925005","https://openalex.org/W2773642388","https://openalex.org/W2776937175","https://openalex.org/W2919115771","https://openalex.org/W2958150439","https://openalex.org/W2963420272","https://openalex.org/W2963470893","https://openalex.org/W2964189045","https://openalex.org/W2979708377","https://openalex.org/W2980030301","https://openalex.org/W2995988442","https://openalex.org/W3004452670","https://openalex.org/W3006379117","https://openalex.org/W3023371261","https://openalex.org/W3046843033","https://openalex.org/W3123126205","https://openalex.org/W3173809883","https://openalex.org/W3193520650","https://openalex.org/W3202403792","https://openalex.org/W4213217404","https://openalex.org/W4220700630","https://openalex.org/W4285123209","https://openalex.org/W4319302797","https://openalex.org/W4367042958"],"related_works":["https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Abstract":[0],"Deep":[1],"learning":[2,32,58,75],"models":[3,18,59],"have":[4],"found":[5],"extensive":[6],"application":[7],"in":[8,13,65,219],"medical":[9],"imaging":[10],"analysis,":[11],"particularly":[12],"mammography":[14,25],"classification.":[15,80,221],"However,":[16],"these":[17],"encounter":[19],"challenges":[20],"associated":[21],"with":[22,174,207],"limited":[23],"annotated":[24],"public":[26,144],"datasets.":[27,148],"In":[28,67],"recent":[29],"years,":[30],"self-supervised":[31,57,74],"(SSL)":[33],"has":[34],"emerged":[35],"as":[36,127],"a":[37,53,72,92,105,130,215,228],"noteworthy":[38],"solution":[39],"to":[40,97,114],"addressing":[41],"data":[42],"scarcity":[43,55],"by":[44,124,233],"leveraging":[45],"pretext":[46,93],"and":[47,146,165,193,214,238],"downstream":[48,111],"tasks.":[49],"Nevertheless,":[50],"we":[51,70],"recognize":[52],"notable":[54],"of":[56,117,137,177,217],"designed":[60,96],"for":[61,77,153,160,179,182,188,191,195],"the":[62,110,115,120,125,138,154,161,201,223],"classification":[63,116,163],"task":[64,94,164],"mammography.":[66],"this":[68],"context,":[69],"propose":[71],"novel":[73],"model":[76,84,140,156,170,203,226],"limited-sample":[78],"mammogram":[79,102,220],"Our":[81],"proposed":[82,139,155,168,202,224],"SSL":[83,169,225],"comprises":[85],"two":[86],"primary":[87],"networks.":[88],"The":[89,135,167],"first":[90],"is":[91,141],"network":[95,230],"learn":[98],"discriminative":[99],"features":[100],"through":[101,129],"reconstruction":[103],"using":[104],"variational":[106],"autoencoder":[107],"(VAE).":[108],"Subsequently,":[109],"network,":[112],"dedicated":[113],"mammograms,":[118],"uses":[119],"encoded":[121],"space":[122],"extracted":[123],"VAE":[126],"input":[128],"simple":[131],"convolutional":[132],"neural":[133],"network.":[134],"performance":[136,173],"assessed":[142],"on":[143,185,198],"INbreast":[145],"MIAS":[147],"Comparative":[149],"analyzes":[150],"are":[151],"conducted":[152],"against":[157],"previous":[158,247],"studies":[159],"same":[162],"dataset.":[166],"demonstrates":[171],"high":[172],"an":[175],"AUC":[176],"0.94":[178],"density,":[180,192],"0.99":[181,190,194],"malignant-nonmalignant":[183],"classifications":[184,197],"INbreast,":[186],"0.97":[187],"benign-malignant,":[189],"normal-benign-malignant":[196],"MIAS.":[199],"Additionally,":[200],"reduces":[204],"computational":[205,244],"costs":[206],"only":[208],"228":[209],"trainable":[210],"parameters,":[211],"204.95K":[212],"FLOPs,":[213],"depth":[216],"3":[218],"Overall,":[222],"exhibits":[227],"robust":[229],"architecture":[231],"characterized":[232],"repeatability,":[234],"consistency,":[235],"generalization":[236],"ability,":[237],"transferability":[239],"among":[240],"datasets,":[241],"providing":[242],"less":[243],"complexity":[245],"than":[246],"studies.":[248],"Graphical":[249],"abstract":[250]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":3}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}