Oral Health Parameter-Based Diabetes Type 2 Indication Using Machine Learning
NCT ID: NCT06981286
Last Updated: 2025-05-20
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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NOT_YET_RECRUITING
2000 participants
OBSERVATIONAL
2025-08-30
2027-07-31
Brief Summary
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Detailed Description
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Objectives:
1. Primary Objective: To assess the potential of oral health parameters for binary classification of type 2 diabetes or not.
2. Secondary Objective: To identify the most influential oral health parameters contributing to type 2 diabetes predictions.
3. Tertiary Objective: To compare the performance of Random Forest (RF), Support Vector Machine (SVM), and CatBoost (CB) classifiers in predicting type 2 diabetes using oral health data.
Conditions
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Study Design
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CASE_CONTROL
CROSS_SECTIONAL
Study Groups
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T2D
Older individuals with Diabetes type 2
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.
Group/Cohort Description: Older individuals without Diabetes type 2
No interventions assigned to this group
Interventions
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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.
Eligibility Criteria
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Inclusion Criteria
* Participants with recorded oral health parameters with or without Diabetes type2
Exclusion Criteria
60 Years
ALL
Yes
Sponsors
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Blekinge Institute of Technology
OTHER
Responsible Party
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Locations
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Department of Health, Blekinge Institute of Technology
Karlskrona, , Sweden
Countries
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Central Contacts
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Facility Contacts
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Role: backup
Other Identifiers
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DT2 prediction
Identifier Type: -
Identifier Source: org_study_id
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