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

Blekinge Institute of Technology

Status: Not yet enrolling

Conditions: Type 2 Diabetes

Treatments: Other: A dataset comprising participants withT2D will be used to evaluate the classification performance of various machine learning techniques.

Study type: Observational

Funder types: Other

Identifiers

NCT06981286

DT2 prediction

Details and patient eligibility

About

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.

Full description

This cross-sectional study utilizes oral health and demographic data from the Swedish National Study on Aging and Care (SNAC-B). Participants aged 60 years or older with Mild Cognitive Impairment will be included in the analysis. The data will be used to develop and evaluate machine learning models for predicting type 2 diabetes.

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.

Enrollment: 2,000 estimated patients

Sex: All

Ages: 60+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Individuals aged 60 years or older.
• Participants with recorded oral health parameters with or without Diabetes type2

Exclusion criteria

• Individuals with Diabetes type1

Trial design

2,000 participants in 2 patient groups

T2D

Description:

Older individuals with Diabetes type 2

Treatment:

Other: A dataset comprising participants withT2D will be used to evaluate the classification performance of various machine learning techniques.

Group/Cohort Description: Older individuals without Diabetes type 2