{"id":"https://openalex.org/W4415124536","doi":"https://doi.org/10.1109/icmlt65785.2025.11193393","title":"Data Valuation with Shapley-based Methods for Medical Image Classification","display_name":"Data Valuation with Shapley-based Methods for Medical Image Classification","publication_year":2025,"publication_date":"2025-05-23","ids":{"openalex":"https://openalex.org/W4415124536","doi":"https://doi.org/10.1109/icmlt65785.2025.11193393"},"language":"en","primary_location":{"id":"doi:10.1109/icmlt65785.2025.11193393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlt65785.2025.11193393","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th International Conference on Machine Learning Technologies (ICMLT)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://acikerisim.fsm.edu.tr/bitstreams/9874856c-dd21-4871-a5af-f3b103c7c5d0/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104987175","display_name":"Zeliha Kaya Ak\u00e7elik","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146544","display_name":"Fatih Sultan Mehmet Waqf University","ror":"https://ror.org/04mma4681","country_code":"TR","type":"education","lineage":["https://openalex.org/I4210146544"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Zeliha Kaya Ak\u00e7elik","raw_affiliation_strings":["Fatih Sultan Mehmet Vakif University,Department of Computer Engineering,&#x0130;stanbul,T&#x00FC;rkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fatih Sultan Mehmet Vakif University,Department of Computer Engineering,&#x0130;stanbul,T&#x00FC;rkiye","institution_ids":["https://openalex.org/I4210146544"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104987177","display_name":"Reyhan Ho\u015favc\u0131","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146544","display_name":"Fatih Sultan Mehmet Waqf University","ror":"https://ror.org/04mma4681","country_code":"TR","type":"education","lineage":["https://openalex.org/I4210146544"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Reyhan Ho\u015favc\u0131","raw_affiliation_strings":["Fatih Sultan Mehmet Vakif University,Department of Biomedical Engineering,&#x0130;stanbul,T&#x00FC;rkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fatih Sultan Mehmet Vakif University,Department of Biomedical Engineering,&#x0130;stanbul,T&#x00FC;rkiye","institution_ids":["https://openalex.org/I4210146544"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116298655","display_name":"S\u00fcmeyye Z\u00fclal Dik","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146544","display_name":"Fatih Sultan Mehmet Waqf University","ror":"https://ror.org/04mma4681","country_code":"TR","type":"education","lineage":["https://openalex.org/I4210146544"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"S\u00fcmeyye Z\u00fclal Dik","raw_affiliation_strings":["Fatih Sultan Mehmet Vakif University,Department of Computer Engineering,&#x0130;stanbul,T&#x00FC;rkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fatih Sultan Mehmet Vakif University,Department of Computer Engineering,&#x0130;stanbul,T&#x00FC;rkiye","institution_ids":["https://openalex.org/I4210146544"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083787764","display_name":"Musa Ayd\u0131n","orcid":"https://orcid.org/0000-0002-5825-2230"},"institutions":[{"id":"https://openalex.org/I4210146544","display_name":"Fatih Sultan Mehmet Waqf University","ror":"https://ror.org/04mma4681","country_code":"TR","type":"education","lineage":["https://openalex.org/I4210146544"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Musa Aydin","raw_affiliation_strings":["Fatih Sultan Mehmet Vakif University,Department of Computer Engineering,&#x0130;stanbul,T&#x00FC;rkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fatih Sultan Mehmet Vakif University,Department of Computer Engineering,&#x0130;stanbul,T&#x00FC;rkiye","institution_ids":["https://openalex.org/I4210146544"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074857800","display_name":"Zeki Ku\u015f","orcid":"https://orcid.org/0000-0001-8762-7233"},"institutions":[{"id":"https://openalex.org/I4210146544","display_name":"Fatih Sultan Mehmet Waqf University","ror":"https://ror.org/04mma4681","country_code":"TR","type":"education","lineage":["https://openalex.org/I4210146544"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Zeki Ku\u015f","raw_affiliation_strings":["Fatih Sultan Mehmet Vakif University,Department of Computer Engineering,&#x0130;stanbul,T&#x00FC;rkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fatih Sultan Mehmet Vakif University,Department of Computer Engineering,&#x0130;stanbul,T&#x00FC;rkiye","institution_ids":["https://openalex.org/I4210146544"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210146544"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23142166,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"461","last_page":"467"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.661300003528595,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.661300003528595,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/valuation","display_name":"Valuation (finance)","score":0.5849999785423279},{"id":"https://openalex.org/keywords/shapley-value","display_name":"Shapley value","score":0.5473999977111816},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.41920000314712524},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.39910000562667847},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.3781999945640564},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.37779998779296875},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.36469998955726624}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7085999846458435},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6044999957084656},{"id":"https://openalex.org/C186027771","wikidata":"https://www.wikidata.org/wiki/Q4008379","display_name":"Valuation (finance)","level":2,"score":0.5849999785423279},{"id":"https://openalex.org/C199022921","wikidata":"https://www.wikidata.org/wiki/Q240046","display_name":"Shapley value","level":3,"score":0.5473999977111816},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4359000027179718},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.41920000314712524},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.39910000562667847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39719998836517334},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3781999945640564},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.37779998779296875},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.36469998955726624},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3059999942779541},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.28450000286102295},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.26429998874664307},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icmlt65785.2025.11193393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlt65785.2025.11193393","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th International Conference on Machine Learning Technologies (ICMLT)","raw_type":"proceedings-article"},{"id":"pmh:oai:acikerisim.fsm.edu.tr:11352/5750","is_oa":true,"landing_page_url":"https://acikerisim.fsm.edu.tr/bitstreams/9874856c-dd21-4871-a5af-f3b103c7c5d0/download","pdf_url":null,"source":{"id":"https://openalex.org/S4306400556","display_name":"DSpace@FSM (FSM Vakif University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210146544","host_organization_name":"Fatih Sultan Mehmet Waqf University","host_organization_lineage":["https://openalex.org/I4210146544"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Object"}],"best_oa_location":{"id":"pmh:oai:acikerisim.fsm.edu.tr:11352/5750","is_oa":true,"landing_page_url":"https://acikerisim.fsm.edu.tr/bitstreams/9874856c-dd21-4871-a5af-f3b103c7c5d0/download","pdf_url":null,"source":{"id":"https://openalex.org/S4306400556","display_name":"DSpace@FSM (FSM Vakif University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210146544","host_organization_name":"Fatih Sultan Mehmet Waqf University","host_organization_lineage":["https://openalex.org/I4210146544"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Object"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,157],"study":[1,158],"introduces":[2],"novel":[3],"approaches":[4,210],"to":[5,25,53,126,177,211],"data":[6,27,51,114,153,161,208,214],"valuation":[7,162,215],"in":[8,105,116,154,164,194],"medical":[9,165],"image":[10,166],"classification,":[11],"focusing":[12],"on":[13,57,77,84],"the":[14,32,47,64,85,106,113,127,135,140,151,171],"Gradient":[15,19,43,66],"Shapley":[16,20,44,67],"and":[17,72,95,188],"Improved":[18,65],"methods.":[21],"These":[22],"methods":[23,91,142,176,205],"aim":[24],"reduce":[26],"selection":[28,209],"costs":[29],"while":[30],"improving":[31],"model":[33,54],"performance,":[34,75],"making":[35],"them":[36],"highly":[37],"practical":[38],"for":[39,191],"training":[40,179],"processes.":[41,216],"The":[42,168],"method":[45,68,190],"evaluates":[46],"contributions":[48],"of":[49,112,120,131,150,173],"individual":[50],"samples":[52],"performance":[55,147],"based":[56],"a":[58,186],"robust":[59],"theoretical":[60],"foundation.":[61],"In":[62,138],"addition,":[63],"enhances":[69],"computational":[70],"efficiency":[71],"demonstrates":[73],"superior":[74],"particularly":[76],"noisy":[78],"or":[79],"imbalanced":[80],"datasets.":[81,156],"Experiments":[82],"conducted":[83],"MedMNIST":[86],"dataset":[87],"reveal":[88],"that":[89],"both":[90],"achieve":[92],"competitive":[93],"accuracy":[94],"AUC":[96,118,129],"values":[97],"even":[98],"with":[99,134,148,206],"significantly":[100,159],"reduced":[101],"data.":[102],"For":[103],"instance,":[104],"PathMNIST":[107],"dataset,":[108],"using":[109],"only":[110],"10%":[111],"resulted":[115],"an":[117],"value":[119,130],"96.6%,":[121],"which":[122],"is":[123],"remarkably":[124],"close":[125],"baseline":[128],"98.3%":[132],"achieved":[133],"full":[136,152],"dataset.":[137],"particular,":[139],"Shapley-based":[141],"have":[143],"shown":[144],"better":[145],"classification":[146],"\u226450%":[149],"some":[155],"improves":[160],"processes":[163,180],"classification.":[167],"findings":[169],"highlight":[170],"potential":[172],"Shapley's":[174],"value-based":[175],"optimize":[178],"without":[181],"sacrificing":[182],"performance.":[183],"They":[184],"offer":[185],"scalable":[187],"efficient":[189],"real-world":[192],"applications":[193],"critical":[195],"domains":[196],"like":[197],"healthcare.":[198],"Future":[199],"research":[200],"could":[201],"explore":[202],"integrating":[203],"these":[204],"other":[207],"further":[212],"enhance":[213]},"counts_by_year":[],"updated_date":"2026-08-25T07:29:55.448023","created_date":"2025-10-14T00:00:00"}
