{"id":"https://openalex.org/W4388937080","doi":"https://doi.org/10.1109/icccnt56998.2023.10306942","title":"Early Detection and Prediction of Diabetes Using Ensemble Classifier","display_name":"Early Detection and Prediction of Diabetes Using Ensemble Classifier","publication_year":2023,"publication_date":"2023-07-06","ids":{"openalex":"https://openalex.org/W4388937080","doi":"https://doi.org/10.1109/icccnt56998.2023.10306942"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt56998.2023.10306942","doi":"https://doi.org/10.1109/icccnt56998.2023.10306942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt56998.2023.10306942","pdf_url":null,"source":{"id":"https://openalex.org/S4306497833","display_name":"International Conference on Computing, Communication and Networking Technologies (ICCCNT)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055155245","display_name":"Yash Prajapati","orcid":"https://orcid.org/0000-0003-0258-1921","observed_orcids":["https://orcid.org/0000-0003-0258-1921"]},"institutions":[{"id":"https://openalex.org/I4405257251","display_name":"LJ University","ror":"https://ror.org/052hbwv48","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405257251"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Yash R Prajapati","raw_affiliation_strings":["L J University,Department of Computer Applications,Ahmedabad","Department of Computer Applications, L J University, Ahmedabad"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"L J University,Department of Computer Applications,Ahmedabad","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Applications, L J University, Ahmedabad","institution_ids":["https://openalex.org/I4405257251"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093323921","display_name":"Darshan G Hihoriya","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405257251","display_name":"LJ University","ror":"https://ror.org/052hbwv48","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405257251"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Darshan G Hihoriya","raw_affiliation_strings":["L J University,Department of Computer Applications,Ahmedabad","Department of Computer Applications, L J University, Ahmedabad"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"L J University,Department of Computer Applications,Ahmedabad","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Applications, L J University, Ahmedabad","institution_ids":["https://openalex.org/I4405257251"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034679216","display_name":"Shanti Verma","orcid":"https://orcid.org/0000-0001-5336-923X","observed_orcids":["https://orcid.org/0000-0001-5336-923X"]},"institutions":[{"id":"https://openalex.org/I4405257251","display_name":"LJ University","ror":"https://ror.org/052hbwv48","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405257251"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shanti Verma","raw_affiliation_strings":["L J University,Department of Computer Applications,Ahmedabad","Department of Computer Applications, L J University, Ahmedabad"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"L J University,Department of Computer Applications,Ahmedabad","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Applications, L J University, Ahmedabad","institution_ids":["https://openalex.org/I4405257251"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4405257251"],"apc_list":null,"apc_paid":null,"fwci":3.427,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.93832127,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9994999766349792,"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":0.9994999766349792,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11140","display_name":"Natural Antidiabetic Agents Studies","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"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/diabetes-prediction","display_name":"diabetes prediction","score":0.9819999933242798},{"id":"https://openalex.org/keywords/early-diagnosis-of-diabetes","display_name":"early detection of diabetes","score":0.7760000228881836},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"ensemble learning","score":0.859000027179718},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.9110000133514404},{"id":"https://openalex.org/keywords/bagging","display_name":"bagging","score":0.9760000109672546},{"id":"https://openalex.org/keywords/boosting","display_name":"boosting","score":0.9990000128746033},{"id":"https://openalex.org/keywords/averaging","display_name":"averaging","score":0.5569999814033508},{"id":"https://openalex.org/keywords/diabetes-risk-factors","display_name":"diabetes risk factors","score":0.6740000247955322},{"id":"https://openalex.org/keywords/blood-pressure","display_name":"blood pressure","score":0.7559999823570251},{"id":"https://openalex.org/keywords/blood-glucose","display_name":"blood glucose","score":0.6809999942779541},{"id":"https://openalex.org/keywords/body-mass-index","display_name":"body mass index","score":0.7429999709129333},{"id":"https://openalex.org/keywords/pregnancy","display_name":"pregnancy","score":0.7129999995231628},{"id":"https://openalex.org/keywords/demographic-data","display_name":"demographic data","score":0.4399999976158142}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7580050230026245},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7142887115478516},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6174060702323914},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.6125960350036621},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5731449127197266},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5595189929008484},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.5471287965774536},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5466918349266052},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4494629502296448},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.41818636655807495},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.41353267431259155},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.41124480962753296},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.281497597694397},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.14063206315040588},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccnt56998.2023.10306942","doi":"https://doi.org/10.1109/icccnt56998.2023.10306942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt56998.2023.10306942","pdf_url":null,"source":{"id":"https://openalex.org/S4306497833","display_name":"International Conference on Computing, Communication and Networking Technologies (ICCCNT)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.9940000176429749,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2512529154","https://openalex.org/W2767472208","https://openalex.org/W2775888755","https://openalex.org/W2925081828","https://openalex.org/W2942185839","https://openalex.org/W2967427280","https://openalex.org/W2994810741","https://openalex.org/W2998217597","https://openalex.org/W3012920614","https://openalex.org/W3035569864","https://openalex.org/W3038606102","https://openalex.org/W3042228882","https://openalex.org/W3046026969","https://openalex.org/W3080667022","https://openalex.org/W3098571227","https://openalex.org/W3104692145","https://openalex.org/W3145139730","https://openalex.org/W3159242155","https://openalex.org/W4311449810"],"related_works":["https://openalex.org/W4393079407","https://openalex.org/W4237612942","https://openalex.org/W4306870411","https://openalex.org/W3110359985","https://openalex.org/W4309643625","https://openalex.org/W4285394323","https://openalex.org/W4313906961","https://openalex.org/W4405678937","https://openalex.org/W4407445287","https://openalex.org/W7128692173"],"abstract_inverted_index":{"Diabetes":[0],"is":[1,12,42,76,96,166,173],"a":[2,13,21,54,139],"chronic":[3],"disease":[4,95],"that":[5,16,151],"affects":[6],"millions":[7],"of":[8,23,39,49,63,101,147,170,199,213],"people":[9],"worldwide.":[10],"It":[11],"complex":[14],"condition":[15],"can":[17],"be":[18],"caused":[19],"by":[20],"variety":[22],"factors,":[24],"including":[25],"pregnancy,":[26,123],"blood":[27,124],"pressure,":[28,125],"glucose":[29,126],"levels,":[30,127],"and":[31,47,91,128,133,184,186,211],"BMI.":[32],"Identifying":[33],"individuals":[34],"who":[35],"are":[36,202],"at":[37],"risk":[38],"developing":[40],"diabetes":[41,68],"crucial":[43],"in":[44,60,69,83,204],"the":[45,64,70,78,84,102,106,148,171,188,200,205],"prevention":[46],"management":[48],"this":[50,87,94,110,214],"disease.":[51,88,215],"According":[52],"to":[53,72,98,104,114],"World":[55],"Health":[56],"Organization":[57],"(WHO)":[58],"report,":[59],"India":[61,75],"8.7%":[62],"population":[65],"suffers":[66],"from":[67,86,93],"20":[71],"70":[73],"years.":[74],"also":[77],"second":[79],"most":[80],"affected":[81],"country":[82],"world":[85],"Early":[89],"detection":[90,212],"prediction":[92,210],"necessary":[97],"help":[99],"citizens":[100],"county":[103],"reduce":[105],"adverse":[107],"conditions.":[108],"In":[109],"paper":[111],"authors":[112,177],"try":[113],"build":[115],"an":[116],"ensemble":[117,179],"classification":[118,152],"model":[119,172],"based":[120],"on":[121,143],"demographics,":[122],"BMI":[129],"using":[130,155],"bagging,":[131],"boosting":[132,185],"averaging":[134,189],"methods.":[135,196],".":[136],"Authors":[137],"used":[138],"secondary":[140],"dataset":[141],"available":[142],"kaggle.com.":[144],"The":[145,168,197],"results":[146,198],"study":[149,201],"says":[150],"models":[153],"built":[154],"random":[156],"forest":[157],"algorithms":[158,164],"have":[159],"higher":[160],"accuracy":[161,169],"than":[162,194],"other":[163,195],"which":[165],"81.1%.":[167],"not":[174],"satisfactory":[175],"so":[176],"applied":[178],"learning":[180],"methods":[181],"averaging,":[182],"bagging":[183],"found":[187],"method":[190],"has":[191],"less":[192],"error":[193],"helpful":[203],"healthcare":[206],"industry":[207],"for":[208],"early":[209]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":10}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2023-11-24T00:00:00"}