{"id":"https://openalex.org/W4391889502","doi":"https://doi.org/10.1109/comsnets59351.2024.10427272","title":"Machine Learning-Based Trustworthy Diabetes Prediction Model","display_name":"Machine Learning-Based Trustworthy Diabetes Prediction Model","publication_year":2024,"publication_date":"2024-01-03","ids":{"openalex":"https://openalex.org/W4391889502","doi":"https://doi.org/10.1109/comsnets59351.2024.10427272"},"language":"en","primary_location":{"id":"doi:10.1109/comsnets59351.2024.10427272","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/comsnets59351.2024.10427272","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS)","raw_type":"proceedings-article"},"type":"article","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/A5038563694","display_name":"Aruna Devi B","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144604","display_name":"ITPEnergised Group (India)","ror":"https://ror.org/04y5qg507","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210114570","https://openalex.org/I4210144604"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Aruna Devi B","raw_affiliation_strings":["National Institute of Technology Puducherry Karaikal,Department of Computer Science and Engineering,Puducherry,India","Department of Computer Science and Engineering, National Institute of Technology Puducherry Karaikal, Puducherry, India"],"affiliations":[{"raw_affiliation_string":"National Institute of Technology Puducherry Karaikal,Department of Computer Science and Engineering,Puducherry,India","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science and Engineering, National Institute of Technology Puducherry Karaikal, Puducherry, India","institution_ids":["https://openalex.org/I4210144604"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065340734","display_name":"N. Karthik","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144604","display_name":"ITPEnergised Group (India)","ror":"https://ror.org/04y5qg507","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210114570","https://openalex.org/I4210144604"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Karthik N","raw_affiliation_strings":["National Institute of Technology Puducherry Karaikal,Department of Computer Science and Engineering,Puducherry,India","Department of Computer Science and Engineering, National Institute of Technology Puducherry Karaikal, Puducherry, India"],"affiliations":[{"raw_affiliation_string":"National Institute of Technology Puducherry Karaikal,Department of Computer Science and Engineering,Puducherry,India","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science and Engineering, National Institute of Technology Puducherry Karaikal, Puducherry, India","institution_ids":["https://openalex.org/I4210144604"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5038563694"],"corresponding_institution_ids":["https://openalex.org/I4210144604"],"apc_list":null,"apc_paid":null,"fwci":0.7247,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.72722703,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"3","issue":null,"first_page":"400","last_page":"402"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9815000295639038,"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":0.9815000295639038,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.8538591861724854},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7329972386360168},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4921233057975769},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47659820318222046},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.16256806254386902}],"concepts":[{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.8538591861724854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7329972386360168},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4921233057975769},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47659820318222046},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.16256806254386902}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/comsnets59351.2024.10427272","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/comsnets59351.2024.10427272","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2125377929","https://openalex.org/W2606991295","https://openalex.org/W2899434936","https://openalex.org/W2908285635","https://openalex.org/W2963613787","https://openalex.org/W2998216295","https://openalex.org/W3005258580","https://openalex.org/W3021448296","https://openalex.org/W3036630507","https://openalex.org/W3156485131","https://openalex.org/W3170657538","https://openalex.org/W4295530411","https://openalex.org/W4386879939"],"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/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Diabetes":[0,14],"is":[1,10,49,57,72,144],"a":[2,53,92,97,147],"condition":[3,62],"that":[4],"develops":[5],"when":[6],"the":[7,17,39,60,105,111,118,125],"blood":[8,34],"sugar":[9,35],"above":[11],"average":[12],"level.":[13],"shoots":[15],"up":[16],"risk":[18],"of":[19,41,107,127,141],"eye,":[20],"kidney,":[21],"nerve,":[22],"and":[23,63,79,88,124,129,155,165],"heart":[24],"problems.":[25],"By":[26],"adopting":[27],"suitable":[28],"measures":[29],"to":[30,145],"prevent":[31],"or":[32,66],"manage":[33],"level":[36],"may":[37],"reduce":[38],"chances":[40],"getting":[42],"diabetes-related":[43],"health":[44],"issues.":[45],"Medical":[46],"data":[47,78,85],"collection":[48],"not":[50],"done":[51],"on":[52,104],"regular":[54],"basis":[55],"but":[56],"determined":[58],"by":[59,109],"patient's":[61],"other":[64],"clinical":[65],"administrative":[67],"factors.":[68],"A":[69],"trustworthy":[70,98,148],"model":[71,89,151],"free":[73],"from":[74],"missing":[75,115],"values,":[76],"faulty":[77],"makes":[80],"reliable":[81],"predictions.":[82],"Factors":[83],"like":[84],"quality,":[86],"anomalies,":[87,128],"selection":[90],"play":[91],"significant":[93],"role":[94],"in":[95,117],"building":[96],"model.":[99],"Hence,":[100],"this":[101,142],"work":[102,143],"concentrates":[103],"prediction":[106,132,150],"diabetes":[108,131,149],"considering":[110],"following":[112],"issues:":[113],"1)":[114],"values":[116],"dataset,":[119],"2)":[120],"an":[121,153],"imbalanced":[122,156],"dataset":[123,157],"presence":[126],"3)":[130],"using":[133,158],"Machine":[134],"learning":[135],"(ML)":[136],"algorithm.":[137],"The":[138],"main":[139],"objective":[140],"propose":[146],"for":[152,162],"incomplete":[154],"ML-based":[159],"imputation,":[160],"techniques":[161],"balancing":[163],"datasets,":[164],"anomaly":[166],"detection.":[167]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}