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Oral Health Parameter-Based Diabetes Type 2 Indication Using Machine Learning

NCT06981286 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 2000

Last updated 2025-05-20

No results posted yet for this study

Summary

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.

Conditions

Interventions

OTHER

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.

Sponsors & Collaborators

  • Blekinge Institute of Technology

    lead OTHER

Eligibility

Min Age
60 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-08-30
Primary Completion
2026-12-31
Completion
2027-07-31

Countries

  • Sweden

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06981286 on ClinicalTrials.gov