{"id":"https://openalex.org/W4413980974","doi":"https://doi.org/10.2196/74116","title":"Synthetic Tabular Data Generation Under Horizontal Federated Learning Environments in Acute Myeloid Leukemia: Case-Based Simulation Study","display_name":"Synthetic Tabular Data Generation Under Horizontal Federated Learning Environments in Acute Myeloid Leukemia: Case-Based Simulation Study","publication_year":2025,"publication_date":"2025-09-04","ids":{"openalex":"https://openalex.org/W4413980974","doi":"https://doi.org/10.2196/74116","pmid":"https://pubmed.ncbi.nlm.nih.gov/41021276","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/12519032"},"language":"en","primary_location":{"id":"doi:10.2196/74116","doi":"https://doi.org/10.2196/74116","is_oa":true,"landing_page_url":"https://doi.org/10.2196/74116","pdf_url":null,"source":{"id":"https://openalex.org/S2764650051","display_name":"JMIR Medical Informatics","issn_l":"2291-9694","issn":["2291-9694"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-d","doyens","jufo-1","ki-jl-1","medline","norway-1","oarl","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320608","host_organization_name":"JMIR Publications","host_organization_lineage":["https://openalex.org/P4310320608"],"host_organization_lineage_names":["JMIR Publications"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"JMIR Medical Informatics","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.2196/74116","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045569794","display_name":"Imanol Isasa","orcid":"https://orcid.org/0000-0002-3031-695X","observed_orcids":["https://orcid.org/0000-0002-3031-695X"]},"institutions":[{"id":"https://openalex.org/I169108374","display_name":"University of the Basque Country","ror":"https://ror.org/000xsnr85","country_code":"ES","type":"education","lineage":["https://openalex.org/I169108374"]},{"id":"https://openalex.org/I4210092551","display_name":"Vicomtech","ror":"https://ror.org/0023sah13","country_code":"ES","type":"facility","lineage":["https://openalex.org/I4210092551"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Imanol Isasa","raw_affiliation_strings":["Computer Science and Artificial Intelligence Department, University of the Basque Country UPV/EHU, Donostia-San Sebasti\u00e1n, Spain","Digital Health & Biomedical Technologies Department, Vicomtech Foundation (BRTA), Donostia-San Sebasti\u00e1n, Spain"],"raw_orcid":"https://orcid.org/0000-0002-3031-695X","affiliations":[{"raw_affiliation_string":"Computer Science and Artificial Intelligence Department, University of the Basque Country UPV/EHU, Donostia-San Sebasti\u00e1n, Spain","institution_ids":["https://openalex.org/I169108374"]},{"raw_affiliation_string":"Digital Health & Biomedical Technologies Department, Vicomtech Foundation (BRTA), Donostia-San Sebasti\u00e1n, Spain","institution_ids":["https://openalex.org/I4210092551"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116782625","display_name":"Mikel Catalina","orcid":"https://orcid.org/0009-0000-2076-8015","observed_orcids":["https://orcid.org/0009-0000-2076-8015"]},"institutions":[{"id":"https://openalex.org/I4210092551","display_name":"Vicomtech","ror":"https://ror.org/0023sah13","country_code":"ES","type":"facility","lineage":["https://openalex.org/I4210092551"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Mikel Catalina","raw_affiliation_strings":["Digital Health & Biomedical Technologies Department, Vicomtech Foundation (BRTA), Donostia-San Sebasti\u00e1n, Spain"],"raw_orcid":"https://orcid.org/0009-0000-2076-8015","affiliations":[{"raw_affiliation_string":"Digital Health & Biomedical Technologies Department, Vicomtech Foundation (BRTA), Donostia-San Sebasti\u00e1n, Spain","institution_ids":["https://openalex.org/I4210092551"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034994292","display_name":"Gorka Epelde","orcid":"https://orcid.org/0000-0002-5179-415X","observed_orcids":["https://orcid.org/0000-0002-5179-415X"]},"institutions":[{"id":"https://openalex.org/I4210092551","display_name":"Vicomtech","ror":"https://ror.org/0023sah13","country_code":"ES","type":"facility","lineage":["https://openalex.org/I4210092551"]},{"id":"https://openalex.org/I4210100188","display_name":"Biogipuzkoa Health Research Institute","ror":"https://ror.org/01a2wsa50","country_code":"ES","type":"facility","lineage":["https://openalex.org/I4210100188"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Gorka Epelde","raw_affiliation_strings":["Digital Health & Biomedical Technologies Department, Vicomtech Foundation (BRTA), Donostia-San Sebasti\u00e1n, Spain","eHealth Group, Biogipuzkoa Health Research Institute, Donostia-San Sebasti\u00e1n, Spain"],"raw_orcid":"https://orcid.org/0000-0002-5179-415X","affiliations":[{"raw_affiliation_string":"Digital Health & Biomedical Technologies Department, Vicomtech Foundation (BRTA), Donostia-San Sebasti\u00e1n, Spain","institution_ids":["https://openalex.org/I4210092551"]},{"raw_affiliation_string":"eHealth Group, Biogipuzkoa Health Research Institute, Donostia-San Sebasti\u00e1n, Spain","institution_ids":["https://openalex.org/I4210100188"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023770749","display_name":"Naiara Aginako","orcid":"https://orcid.org/0000-0002-2156-8215","observed_orcids":["https://orcid.org/0000-0002-2156-8215"]},"institutions":[{"id":"https://openalex.org/I169108374","display_name":"University of the Basque Country","ror":"https://ror.org/000xsnr85","country_code":"ES","type":"education","lineage":["https://openalex.org/I169108374"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Naiara Aginako","raw_affiliation_strings":["Computer Science and Artificial Intelligence Department, University of the Basque Country UPV/EHU, Donostia-San Sebasti\u00e1n, Spain"],"raw_orcid":"https://orcid.org/0000-0002-2156-8215","affiliations":[{"raw_affiliation_string":"Computer Science and Artificial Intelligence Department, University of the Basque Country UPV/EHU, Donostia-San Sebasti\u00e1n, Spain","institution_ids":["https://openalex.org/I169108374"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052326707","display_name":"Andoni Beristain","orcid":"https://orcid.org/0000-0002-5452-2141","observed_orcids":["https://orcid.org/0000-0002-5452-2141"]},"institutions":[{"id":"https://openalex.org/I169108374","display_name":"University of the Basque Country","ror":"https://ror.org/000xsnr85","country_code":"ES","type":"education","lineage":["https://openalex.org/I169108374"]},{"id":"https://openalex.org/I4210092551","display_name":"Vicomtech","ror":"https://ror.org/0023sah13","country_code":"ES","type":"facility","lineage":["https://openalex.org/I4210092551"]},{"id":"https://openalex.org/I4210100188","display_name":"Biogipuzkoa Health Research Institute","ror":"https://ror.org/01a2wsa50","country_code":"ES","type":"facility","lineage":["https://openalex.org/I4210100188"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Andoni Beristain","raw_affiliation_strings":["Computer Science and Artificial Intelligence Department, University of the Basque Country UPV/EHU, Donostia-San Sebasti\u00e1n, Spain","Digital Health & Biomedical Technologies Department, Vicomtech Foundation (BRTA), Donostia-San Sebasti\u00e1n, Spain","eHealth Group, Biogipuzkoa Health Research Institute, Donostia-San Sebasti\u00e1n, Spain"],"raw_orcid":"https://orcid.org/0000-0002-5452-2141","affiliations":[{"raw_affiliation_string":"Computer Science and Artificial Intelligence Department, University of the Basque Country UPV/EHU, Donostia-San Sebasti\u00e1n, Spain","institution_ids":["https://openalex.org/I169108374"]},{"raw_affiliation_string":"Digital Health & Biomedical Technologies Department, Vicomtech Foundation (BRTA), Donostia-San Sebasti\u00e1n, Spain","institution_ids":["https://openalex.org/I4210092551"]},{"raw_affiliation_string":"eHealth Group, Biogipuzkoa Health Research Institute, Donostia-San Sebasti\u00e1n, Spain","institution_ids":["https://openalex.org/I4210100188"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5045569794"],"corresponding_institution_ids":["https://openalex.org/I169108374","https://openalex.org/I4210092551"],"apc_list":{"value":2300,"currency":"USD","value_usd":2300},"apc_paid":{"value":2300,"currency":"USD","value_usd":2300},"fwci":0.2487,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50424563,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"13","issue":null,"first_page":"e74116","last_page":"e74116"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/T14509","display_name":"demographic modeling and climate adaptation","score":0.0,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/synthetic-tabular-data-generation","display_name":"synthetic tabular data generation","score":0.8949999809265137},{"id":"https://openalex.org/keywords/horizontal-federated-learning","display_name":"horizontal federated learning","score":0.9430000185966492},{"id":"https://openalex.org/keywords/acute-myeloid-leukemia","display_name":"acute myeloid leukemia","score":0.9879999756813049},{"id":"https://openalex.org/keywords/data-scarcity","display_name":"data scarcity","score":0.6430000066757202},{"id":"https://openalex.org/keywords/data-privacy","display_name":"data privacy","score":0.5799999833106995},{"id":"https://openalex.org/keywords/data-fidelity","display_name":"data fidelity","score":0.9290000200271606},{"id":"https://openalex.org/keywords/ctgan","display_name":"CTGAN","score":0.8939999938011169},{"id":"https://openalex.org/keywords/rare-diseases","display_name":"rare diseases","score":0.5569999814033508},{"id":"https://openalex.org/keywords/non-iid-data","display_name":"non-IID data","score":0.6299999952316284},{"id":"https://openalex.org/keywords/synthetic-data-quality-evaluation","display_name":"synthetic data quality evaluation","score":0.5920000076293945},{"id":"https://openalex.org/keywords/hematologic-disorders","display_name":"hematologic disorders","score":0.4359999895095825}],"concepts":[{"id":"https://openalex.org/C43169469","wikidata":"https://www.wikidata.org/wiki/Q580922","display_name":"Preprint","level":2,"score":0.8310636878013611},{"id":"https://openalex.org/C2778729363","wikidata":"https://www.wikidata.org/wiki/Q11688946","display_name":"Myeloid leukemia","level":2,"score":0.668677031993866},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6192774772644043},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3522822856903076},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.3354358673095703},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.308214008808136},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2493819296360016},{"id":"https://openalex.org/C502942594","wikidata":"https://www.wikidata.org/wiki/Q3421914","display_name":"Cancer research","level":1,"score":0.1376602053642273}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000098407","descriptor_name":"Federated Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","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":"D015470","descriptor_name":"Leukemia, Myeloid, Acute","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":6,"locations":[{"id":"doi:10.2196/74116","doi":"https://doi.org/10.2196/74116","is_oa":true,"landing_page_url":"https://doi.org/10.2196/74116","pdf_url":null,"source":{"id":"https://openalex.org/S2764650051","display_name":"JMIR Medical Informatics","issn_l":"2291-9694","issn":["2291-9694"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-d","doyens","jufo-1","ki-jl-1","medline","norway-1","oarl","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320608","host_organization_name":"JMIR Publications","host_organization_lineage":["https://openalex.org/P4310320608"],"host_organization_lineage_names":["JMIR Publications"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"JMIR Medical Informatics","raw_type":"journal-article"},{"id":"doi:10.2196/preprints.74116","doi":"https://doi.org/10.2196/preprints.74116","is_oa":true,"landing_page_url":"https://doi.org/10.2196/preprints.74116","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},{"id":"pmh:oai:pubmedcentral.nih.gov:12519032","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12519032/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12519032/pdf/","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"JMIR Med Inform","raw_type":"Text"},{"id":"pmh:oai:europepmc.org:11326776","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12519032","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"Text"},{"id":"pmid:41021276","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41021276","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,"listed_in":[],"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":"JMIR medical informatics","raw_type":"Journal Article"},{"id":"pmh:oai:doaj.org/article:2843a97246d94137979323bf1f1a155f","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/2843a97246d94137979323bf1f1a155f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"JMIR Medical Informatics, Vol 13, p e74116 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.2196/74116","doi":"https://doi.org/10.2196/74116","is_oa":true,"landing_page_url":"https://doi.org/10.2196/74116","pdf_url":null,"source":{"id":"https://openalex.org/S2764650051","display_name":"JMIR Medical Informatics","issn_l":"2291-9694","issn":["2291-9694"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-d","doyens","jufo-1","ki-jl-1","medline","norway-1","oarl","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320608","host_organization_name":"JMIR Publications","host_organization_lineage":["https://openalex.org/P4310320608"],"host_organization_lineage_names":["JMIR Publications"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"JMIR Medical Informatics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.6240000128746033,"id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G29571876","display_name":null,"funder_award_id":"101095530","funder_id":"https://openalex.org/F4320334322","funder_display_name":"HORIZON EUROPE Framework Programme"},{"id":"https://openalex.org/G4462577783","display_name":"Synthetic generation of hematological data over federated computing frameworks","funder_award_id":"101095530","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320334322","display_name":"HORIZON EUROPE Framework Programme","ror":null},{"id":"https://openalex.org/F8712659396","display_name":"European Health and Digital Executive Agency","ror":"https://ror.org/03xxypa75"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4413980974.pdf","grobid_xml":"https://content.openalex.org/works/W4413980974.grobid-xml"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W2104933073","https://openalex.org/W2289411369","https://openalex.org/W2339658711","https://openalex.org/W2541884796","https://openalex.org/W2565167788","https://openalex.org/W2763518948","https://openalex.org/W2902287545","https://openalex.org/W2902546992","https://openalex.org/W2914437582","https://openalex.org/W2946317738","https://openalex.org/W3015598833","https://openalex.org/W3036033661","https://openalex.org/W3037352346","https://openalex.org/W3038932755","https://openalex.org/W3096831136","https://openalex.org/W3185120262","https://openalex.org/W3204342778","https://openalex.org/W3215867059","https://openalex.org/W4206486197","https://openalex.org/W4214841549","https://openalex.org/W4221148897","https://openalex.org/W4224022798","https://openalex.org/W4239312994","https://openalex.org/W4246527035","https://openalex.org/W4252608096","https://openalex.org/W4287332481","https://openalex.org/W4289944129","https://openalex.org/W4290648657","https://openalex.org/W4310108083","https://openalex.org/W4313644512","https://openalex.org/W4315435229","https://openalex.org/W4323349011","https://openalex.org/W4360884927","https://openalex.org/W4382237561","https://openalex.org/W4382654837","https://openalex.org/W4384521895","https://openalex.org/W4387723908","https://openalex.org/W4387764971","https://openalex.org/W4390619546","https://openalex.org/W4390665506","https://openalex.org/W4390872225","https://openalex.org/W4390897376","https://openalex.org/W4392901776","https://openalex.org/W4393026481","https://openalex.org/W4394824233","https://openalex.org/W4394866898","https://openalex.org/W4395065217","https://openalex.org/W4396754825","https://openalex.org/W4399291454","https://openalex.org/W4399866885","https://openalex.org/W4399881288","https://openalex.org/W4399938968","https://openalex.org/W4400200780","https://openalex.org/W4400438459","https://openalex.org/W4402495237","https://openalex.org/W4404459777","https://openalex.org/W4405385684","https://openalex.org/W4406430067","https://openalex.org/W4406676375","https://openalex.org/W4409746746","https://openalex.org/W4410062040","https://openalex.org/W4417189833","https://openalex.org/W6931544374"],"related_works":["https://openalex.org/W4417013797","https://openalex.org/W6908912979","https://openalex.org/W4406676375","https://openalex.org/W4393026481","https://openalex.org/W7112897766","https://openalex.org/W7204238563","https://openalex.org/W4388048226","https://openalex.org/W4221148897","https://openalex.org/W7128435796","https://openalex.org/W3209061033"],"abstract_inverted_index":{"BACKGROUND:":[0],"Data":[1],"scarcity":[2],"and":[3,76,95,111,124,147,186,191,198,225,256,303],"dispersion":[4],"pose":[5],"significant":[6,243,387],"obstacles":[7],"in":[8,59,80,119,249,260,289,326,337,376],"biomedical":[9],"research,":[10],"particularly":[11],"when":[12],"addressing":[13],"rare":[14,88],"diseases.":[15],"In":[16],"such":[17],"scenarios,":[18,208],"synthetic":[19],"data":[20,58,121,162,170,183,201,228,341,381],"generation":[21],"(SDG)":[22],"has":[23],"emerged":[24],"as":[25,359,392],"a":[26,38,48,87,156,165,178,193,209,233,338],"promising":[27],"path":[28],"to":[29,46,107,221,232,247,258,265,344,365],"mitigate":[30],"the":[31,57,64,72,81,96,99,109,161,169,182,206,226,250,261,266,319,322,329,345,360,367,390],"first":[32],"issue.":[33],"Concurrently,":[34],"federated":[35,77,166,179,194,207,271],"learning":[36,40,78],"is":[37,54],"machine":[39],"paradigm":[41],"where":[42,168,181],"multiple":[43],"nodes":[44,363],"collaborate":[45],"create":[47],"centralized":[49,133],"model":[50,263],"with":[51,125,132,159,196,274],"knowledge":[52],"that":[53],"distilled":[55],"from":[56],"different":[60,120,126,153,175,380],"nodes,":[61,129,176,278],"but":[62],"without":[63],"need":[65],"for":[66,397],"sharing":[67],"it.":[68],"This":[69,104],"research":[70],"explores":[71],"combination":[73],"of":[74,83,98,114,128,205,212,277,301,306,321,331,340,362],"SDG":[75,117,135,334],"technologies":[79],"context":[82],"acute":[84],"myeloid":[85],"leukemia,":[86],"hematological":[89],"disorder,":[90],"evaluating":[91],"their":[92],"combined":[93],"impact":[94,113],"quality":[97],"generated":[100,227],"artificial":[101],"datasets.":[102],"OBJECTIVE:":[103],"study":[105],"aims":[106],"evaluate":[108],"privacy-":[110],"fidelity-related":[112],"horizontally":[115,332],"federating":[116,333],"models":[118,368],"distribution":[122,383],"scenarios":[123],"numbers":[127,276],"comparing":[130,270],"them":[131],"baseline":[134,158,347],"models.":[136],"METHODS:":[137],"Two":[138],"state-of-the-art":[139],"generative":[140,144,253],"models,":[141,310],"conditional":[142,251],"tabular":[143,252],"adversarial":[145,254],"network":[146,255],"FedTabDiff,":[148],"were":[149,171,184,229,282,294,313,374,395],"trained":[150,273],"considering":[151],"four":[152],"scenarios:":[154],"(1)":[155],"nonfederated":[157,346],"all":[160,398],"available,":[163],"(2)":[164],"scenario":[167,180,195,325],"evenly":[172],"distributed":[173,188,200],"among":[174],"(3)":[177],"unevenly":[185],"randomly":[187],"(imbalanced":[189],"data),":[190],"(4)":[192],"nonindependent":[197],"identically":[199],"distributions.":[202],"For":[203],"each":[204],"fixed":[210],"set":[211],"node":[213],"quantities":[214],"(3,":[215],"5,":[216],"7,":[217],"10)":[218],"was":[219],"considered":[220],"assess":[222],"its":[223],"impact,":[224],"evaluated,":[230],"attending":[231],"fidelity-privacy":[234],"trade-off.":[235],"RESULTS:":[236],"The":[237,379],"computed":[238],"fidelity":[239,342],"metrics":[240,293],"exhibited":[241],"statistically":[242,315],"deteriorations":[244,305],"(P<.001)":[245],"up":[246,257],"21%":[248],"62%":[259],"FedTabDiff":[262],"due":[264],"federation":[267],"process.":[268],"When":[269],"experiments":[272],"diverse":[275],"no":[279,386],"strong":[280],"tendencies":[281,394],"observed,":[283],"even":[284,370],"if":[285],"specific":[286,377],"comparisons":[287],"resulted":[288],"significative":[290,372],"differences.":[291],"Privacy":[292],"mainly":[295],"maintained":[296],"while":[297,348],"obtaining":[298],"maximum":[299,304],"improvements":[300],"55%":[302],"26%":[307],"between":[308],"both":[309],"although":[311],"they":[312],"not":[314,356],"significant.":[316],"CONCLUSIONS:":[317],"Within":[318],"scope":[320],"use":[323],"case":[324],"this":[327,353],"paper,":[328],"act":[330],"algorithms":[335],"results":[336],"loss":[339],"compared":[343],"maintaining":[349],"privacy":[350],"levels.":[351],"However,":[352],"deterioration":[354],"does":[355],"significantly":[357],"increase":[358],"number":[361],"used":[364],"train":[366],"grows,":[369],"though":[371],"differences":[373],"found":[375,396],"comparisons.":[378],"partition":[382],"configurations":[384],"had":[385],"effect":[388],"on":[389],"metrics,":[391],"similar":[393],"scenarios.":[399]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2025-09-05T00:00:00"}