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Prediction of MMSE Scores for Cognitive Impairment

NCT06611475 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 693

Last updated 2024-11-25

No results posted yet for this study

Summary

This study aims to explore the potential of using machine learning (ML) algorithms to predict cognitive status, specifically MMSE scores, 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 MMSE scores of 30 (normal cognition) or ≤26 (cognitive impairment) in individuals aged 60 and above.

Conditions

Interventions

OTHER

MMSE ≤26

A dataset comprising participants with MMSE scores of ≤26 and 30 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
2024-06-10
Primary Completion
2024-10-10
Completion
2024-11-10

Countries

  • Sweden

Study Locations

More Related Trials

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 NCT06611475 on ClinicalTrials.gov