[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100591504":3},{"organization":4,"armGroups":7,"interventions":16,"overallOfficials":10,"centralContacts":21,"locations":27,"responsibleParty":48,"collaborators":10,"id":50,"slug":51,"hasResults":52,"nctId":53,"briefTitle":54,"officialTitle":55,"acronym":56,"eligibilityCriteria":57,"healthyVolunteers":58,"sex":59,"minAge":60,"maxAge":10,"enrollmentInfo":61,"targetDuration":64,"studyType":65,"phases":10,"briefSummary":66,"conditions":67,"keywords":69,"overallStatus":73,"whyStopped":10,"lastUpdateSubmitDate":74,"lastUpdatePostDateStruct":75,"startDateStruct":78,"completionDateStruct":80,"leadSponsor":82,"locationsCount":83},{"fullName":5,"class":6},"Blekinge Institute of Technology","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"T2D",null,"Older individuals with Diabetes type 2",[13],"Other: A dataset comprising participants withT2D will be used to evaluate the classification performance of various machine learning techniques.",{"label":15,"type":10,"description":10,"interventionNames":10},"Group\u002FCohort Description: Older individuals without Diabetes type 2",[17],{"type":6,"name":18,"description":19,"armGroupLabels":20,"otherNames":10},"A dataset comprising participants withT2D will be used to evaluate the classification performance of various machine learning techniques.","A dataset comprising participants with T2D will be used to evaluate the classification performance of various machine-learning techniques.",[9],[22],{"name":23,"role":24,"phone":25,"phoneExt":10,"email":26},"Johan Flyborg, DDS, PhD","CONTACT","+46707283117","johan.flyborg@bth.se",[28],{"facility":29,"status":10,"city":30,"state":10,"zip":31,"country":32,"countryCode":33,"cosmosGeoPoint":34,"geoPoint":39,"contacts":40},"Department of Health, Blekinge Institute of Technology","Karlskrona","37179","Sweden","SE",{"type":35,"coordinates":36},"Point",[37,38],15.58661,56.16156,{"lat":38,"lon":37},[41,44,45],{"name":42,"role":24,"phone":43,"phoneExt":10,"email":26},"Johan Flyborg","0707283117",{"name":10,"role":24,"phone":10,"phoneExt":10,"email":26},{"name":46,"role":47,"phone":10,"phoneExt":10,"email":10},"Johan Flyborg, DDS,PhD","PRINCIPAL_INVESTIGATOR",{"type":49,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100591504","oral-health-parameter-based-diabetes-type-2-indication-using-machine-learning-100591504",false,"NCT06981286","Oral Health Parameter-Based Diabetes Type 2 Indication Using Machine Learning","Oral Health Parameter-Based Diabetes Type 2 Indication Using Machine Learning in Older Individuals With Mild Cognitive Impairment","JFG","Inclusion Criteria:\n\n* Individuals aged 60 years or older.\n* Participants with recorded oral health parameters with or without Diabetes type2\n\nExclusion Criteria:\n\n• Individuals with Diabetes type1",true,"ALL","60 Years",{"count":62,"type":63},2000,"ESTIMATED","1 Day","OBSERVATIONAL","This study aims to explore the potential of using machine learning (ML) algorithms to predict Diabetes type2, based on oral health and demographic data. The objective is to evaluate the effectiveness of various ML models and identify the most relevant oral health indicators for predicting type 2 diabetes in individuals with mild cognitive impairment aged 60 and above.",[68],"Type 2 Diabetes",[70,71,72],"Oral Health","Machine Learning","Diabetes Type 2","NOT_YET_RECRUITING","2025-05-19",{"date":76,"type":77},"2025-05-20","ACTUAL",{"date":79,"type":63},"2025-08-30",{"date":81,"type":63},"2027-07",{"name":5,"class":6},1]