{"id":"https://openalex.org/W4211253314","doi":"https://doi.org/10.1186/s12911-022-01775-z","title":"Diabetes mellitus risk prediction in the presence of class imbalance using flexible machine learning methods","display_name":"Diabetes mellitus risk prediction in the presence of class imbalance using flexible machine learning methods","publication_year":2022,"publication_date":"2022-02-10","ids":{"openalex":"https://openalex.org/W4211253314","doi":"https://doi.org/10.1186/s12911-022-01775-z","pmid":"https://pubmed.ncbi.nlm.nih.gov/35139846"},"language":"en","primary_location":{"id":"doi:10.1186/s12911-022-01775-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-022-01775-z","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/track/pdf/10.1186/s12911-022-01775-z","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","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":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcmedinformdecismak.biomedcentral.com/track/pdf/10.1186/s12911-022-01775-z","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102941572","display_name":"Somayeh Sadeghi","orcid":"https://orcid.org/0009-0008-7289-0117"},"institutions":[{"id":"https://openalex.org/I70640408","display_name":"Tehran University of Medical Sciences","ror":"https://ror.org/01c4pz451","country_code":"IR","type":"education","lineage":["https://openalex.org/I70640408"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Somayeh Sadeghi","raw_affiliation_strings":["Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P.O. Box 14155-6446, Tehran, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P.O. Box 14155-6446, Tehran, Iran","institution_ids":["https://openalex.org/I70640408"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091734774","display_name":"Davood Khalili","orcid":"https://orcid.org/0000-0003-4956-1039"},"institutions":[{"id":"https://openalex.org/I4210106249","display_name":"Research Institute for Endocrine Sciences","ror":"https://ror.org/01kpm1136","country_code":"IR","type":"facility","lineage":["https://openalex.org/I4210106249"]},{"id":"https://openalex.org/I58048189","display_name":"Shahid Beheshti University of Medical Sciences","ror":"https://ror.org/034m2b326","country_code":"IR","type":"education","lineage":["https://openalex.org/I58048189"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Davood Khalili","raw_affiliation_strings":["Department of Biostatistics and Epidemiology, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran","Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics and Epidemiology, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran","institution_ids":["https://openalex.org/I4210106249","https://openalex.org/I58048189"]},{"raw_affiliation_string":"Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran","institution_ids":["https://openalex.org/I4210106249","https://openalex.org/I58048189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052148028","display_name":"Azra Ramezankhani","orcid":"https://orcid.org/0000-0002-0850-7258"},"institutions":[{"id":"https://openalex.org/I4210106249","display_name":"Research Institute for Endocrine Sciences","ror":"https://ror.org/01kpm1136","country_code":"IR","type":"facility","lineage":["https://openalex.org/I4210106249"]},{"id":"https://openalex.org/I58048189","display_name":"Shahid Beheshti University of Medical Sciences","ror":"https://ror.org/034m2b326","country_code":"IR","type":"education","lineage":["https://openalex.org/I58048189"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Azra Ramezankhani","raw_affiliation_strings":["Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran","institution_ids":["https://openalex.org/I4210106249","https://openalex.org/I58048189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023683073","display_name":"Mohammad Al\u00ec Mansournia","orcid":"https://orcid.org/0000-0003-3343-2718"},"institutions":[{"id":"https://openalex.org/I70640408","display_name":"Tehran University of Medical Sciences","ror":"https://ror.org/01c4pz451","country_code":"IR","type":"education","lineage":["https://openalex.org/I70640408"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Mohammad Ali Mansournia","raw_affiliation_strings":["Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P.O. Box 14155-6446, Tehran, Iran. mansournia_ma@yahoo.com","Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P.O. Box 14155-6446, Tehran, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P.O. Box 14155-6446, Tehran, Iran. mansournia_ma@yahoo.com","institution_ids":["https://openalex.org/I70640408"]},{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P.O. Box 14155-6446, Tehran, Iran","institution_ids":["https://openalex.org/I70640408"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088464143","display_name":"Mahboubeh Parsaeian","orcid":"https://orcid.org/0000-0003-1928-5424"},"institutions":[{"id":"https://openalex.org/I70640408","display_name":"Tehran University of Medical Sciences","ror":"https://ror.org/01c4pz451","country_code":"IR","type":"education","lineage":["https://openalex.org/I70640408"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Mahboubeh Parsaeian","raw_affiliation_strings":["Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P.O. Box 14155-6446, Tehran, Iran. mahbobehparsaeian@yahoo.com","Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P.O. Box 14155-6446, Tehran, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P.O. Box 14155-6446, Tehran, Iran. mahbobehparsaeian@yahoo.com","institution_ids":["https://openalex.org/I70640408"]},{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P.O. Box 14155-6446, Tehran, Iran","institution_ids":["https://openalex.org/I70640408"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5023683073","https://openalex.org/A5088464143"],"corresponding_institution_ids":["https://openalex.org/I70640408"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":{"value":2690,"currency":"USD","value_usd":2690},"fwci":12.523,"has_fulltext":true,"cited_by_count":66,"citation_normalized_percentile":{"value":0.98522081,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"22","issue":"1","first_page":"36","last_page":"36"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.8567000031471252,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.8567000031471252,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.07639999687671661,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.00839999970048666,"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/health-informatics","display_name":"Health informatics","score":0.7450796961784363},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.6423614621162415},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6226401329040527},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5382248163223267},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5287007093429565},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5219827890396118},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3983483910560608},{"id":"https://openalex.org/keywords/public-health","display_name":"Public health","score":0.18915998935699463},{"id":"https://openalex.org/keywords/nursing","display_name":"Nursing","score":0.09855633974075317}],"concepts":[{"id":"https://openalex.org/C145642194","wikidata":"https://www.wikidata.org/wiki/Q870895","display_name":"Health informatics","level":3,"score":0.7450796961784363},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.6423614621162415},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6226401329040527},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5382248163223267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5287007093429565},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5219827890396118},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3983483910560608},{"id":"https://openalex.org/C138816342","wikidata":"https://www.wikidata.org/wiki/Q189603","display_name":"Public health","level":2,"score":0.18915998935699463},{"id":"https://openalex.org/C159110408","wikidata":"https://www.wikidata.org/wiki/Q121176","display_name":"Nursing","level":1,"score":0.09855633974075317},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003920","descriptor_name":"Diabetes Mellitus","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003920","descriptor_name":"Diabetes Mellitus","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003920","descriptor_name":"Diabetes Mellitus","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","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":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007492","descriptor_name":"Iran","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007492","descriptor_name":"Iran","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007492","descriptor_name":"Iran","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12911-022-01775-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-022-01775-z","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/track/pdf/10.1186/s12911-022-01775-z","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","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":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},{"id":"pmid:35139846","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35139846","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,"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":"BMC medical informatics and decision making","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:8830137","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8830137","pdf_url":null,"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,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Med Inform Decis Mak","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:6595aff926744a74bba144cceb0d9d85","is_oa":true,"landing_page_url":"https://doaj.org/article/6595aff926744a74bba144cceb0d9d85","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,"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":"BMC Medical Informatics and Decision Making, Vol 22, Iss 1, Pp 1-12 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s12911-022-01775-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-022-01775-z","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/track/pdf/10.1186/s12911-022-01775-z","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","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":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.550000011920929}],"awards":[],"funders":[{"id":"https://openalex.org/F4320323457","display_name":"Shahid Beheshti University of Medical Sciences","ror":"https://ror.org/034m2b326"},{"id":"https://openalex.org/F4320335243","display_name":"Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences","ror":"https://ror.org/034m2b326"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4211253314.pdf","grobid_xml":"https://content.openalex.org/works/W4211253314.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W571200655","https://openalex.org/W1976526581","https://openalex.org/W1995443851","https://openalex.org/W2015452969","https://openalex.org/W2055191986","https://openalex.org/W2071164259","https://openalex.org/W2083979043","https://openalex.org/W2137959503","https://openalex.org/W2148143831","https://openalex.org/W2168508521","https://openalex.org/W2264375300","https://openalex.org/W2295598076","https://openalex.org/W2338318698","https://openalex.org/W2487770199","https://openalex.org/W2562319768","https://openalex.org/W2767106145","https://openalex.org/W2888482389","https://openalex.org/W2918408501","https://openalex.org/W2944880943","https://openalex.org/W2974911641","https://openalex.org/W2980444207","https://openalex.org/W2980506460","https://openalex.org/W2999376617","https://openalex.org/W3094699490","https://openalex.org/W3107335993","https://openalex.org/W3111212874","https://openalex.org/W3111251354","https://openalex.org/W3126232929","https://openalex.org/W3134623575","https://openalex.org/W3163266420","https://openalex.org/W4230683138","https://openalex.org/W4243367342","https://openalex.org/W4247993926","https://openalex.org/W4256361765"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4313488044","https://openalex.org/W3209574120","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"BACKGROUND:":[0],"Early":[1],"detection":[2],"and":[3,49,64,78,105,112,130,143,161,165,183,193,205,229],"prediction":[4,33],"of":[5,25,34,72,109,124],"type":[6],"two":[7],"diabetes":[8,26,36,59],"mellitus":[9],"incidence":[10,23],"by":[11,224],"baseline":[12],"measurements":[13],"could":[14],"reduce":[15],"associated":[16],"complications":[17],"in":[18,27,56,61,89,99,107,114,128,132,141,146,178,191,200,208,235],"the":[19,96,122,150,155,221],"future.":[20],"The":[21,70],"low":[22],"rate":[24],"comparison":[28,236],"with":[29,95,237],"non-diabetes":[30],"makes":[31],"accurate":[32],"minority":[35,58],"class":[37,60,84,245],"more":[38],"challenging.":[39],"METHODS:":[40],"Deep":[41],"neural":[42],"network":[43],"(DNN),":[44],"extremely":[45],"gradient":[46],"boosting":[47],"(XGBoost),":[48],"random":[50],"forest":[51],"(RF)":[52],"performance":[53,127,254],"is":[54],"compared":[55,88],"predicting":[57,100],"Tehran":[62],"Lipid":[63],"Glucose":[65],"Study":[66],"(TLGS)":[67],"cohort":[68],"data.":[69,117],"impact":[71],"changing":[73,230],"threshold,":[74],"cost-sensitive":[75,144],"learning,":[76],"over":[77],"under-sampling":[79,140,250],"strategies":[80],"as":[81,232],"solutions":[82,152,242],"to":[83,153,172,188,197,214,243],"imbalance":[85,156,226],"have":[86],"been":[87],"improving":[90],"algorithms":[91,148],"performance.":[92],"RESULTS:":[93],"DNN":[94,142],"highest":[97],"accuracy":[98],"diabetes,":[101],"54.8%,":[102],"outperformed":[103],"XGBoost":[104],"RF":[106,209],"terms":[108],"AUROC,":[110],"g-mean,":[111,129],"f1-measure":[113,125,131,166,184],"original":[115],"imbalanced":[116],"Changing":[118],"threshold":[119,231],"based":[120],"on":[121],"maximum":[123],"improved":[126,181],"three":[133],"algorithms.":[134],"Repeated":[135],"edited":[136],"nearest":[137],"neighbors":[138],"(RENN)":[139],"learning":[145],"tree-based":[147],"were":[149],"best":[151],"tackle":[154],"issue.":[157],"RENN":[158],"increased":[159,210],"ROC":[160,204],"Precision-Recall":[162,206],"AUCs,":[163],"g-mean":[164,182],"from":[167,185,194,211],"0.857,":[168],"0.603,":[169],"0.713,":[170],"0.575":[171],"0.862,":[173],"0.608,":[174],"0.773,":[175],"0.583,":[176],"respectively":[177],"DNN.":[179],"Weighing":[180,228],"0.667,":[186],"0.554":[187],"0.776,":[189],"0.588":[190],"XGBoost,":[192],"0.659,":[195],"0.543":[196],"0.775,":[198],"0.566":[199],"RF,":[201],"respectively.":[202,217],"Also,":[203],"AUCs":[207],"0.840,":[212],"0.578":[213],"0.846,":[215],"0.591,":[216],"CONCLUSION:":[218],"G-mean":[219],"experienced":[220],"most":[222],"increase":[223],"all":[225],"solutions.":[227],"efficient":[233],"strategies,":[234,249],"resampling":[238],"methods":[239,251],"are":[240],"faster":[241],"handle":[244],"imbalance.":[246],"Among":[247],"sampling":[248],"had":[252],"better":[253],"than":[255],"others.":[256]},"counts_by_year":[{"year":2026,"cited_by_count":15},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":12}],"updated_date":"2026-08-14T07:06:38.338062","created_date":"2025-10-10T00:00:00"}