Prediction of Mini-Mental State Examination Scores for Cognitive Impairment and Machine Learning Analysis of Oral Health and Demographic Data Among Individuals Older Than 60 Years: Cross-Sectional Study
The oral health parameters and demographic data used as inputs for ML classifiers contain sufficient information to differentiate between MMSE scores ≤26 and 30. This study suggests oral health parameters and ML techniques could offer a potential tool for screening MMSE scores for individuals aged 60 years and older.
Authors
- Sarah Nauman Ghazi (ORCID: https://orcid.org/0000-0001-8114-8813)
- Ana Luiza Dallora (ORCID: https://orcid.org/0000-0002-6752-017X)
- Elina Mikaelsson Midlöv (ORCID: https://orcid.org/0000-0002-2782-147X)
- Alper Idrisoglu (ORCID: https://orcid.org/0000-0003-1558-2309)
- Anna Axén (ORCID: https://orcid.org/0000-0002-1509-4631)
- Helén Dellkvist (ORCID: https://orcid.org/0000-0002-9261-4784)
- Johan Flyborg (ORCID: https://orcid.org/0000-0001-9148-9582)
Institutions
- Blekinge Institute of Technology (SE)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2025-08-25
- DOI
- https://doi.org/10.2196/75069
- Primary Topic
- Dental Health and Care Utilization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Blekinge Tekniska Högskola