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A toolbox for the processing of cognitive tests for the assessment of the Alzheimer's disease

Debelle, Anouk
(2024)

Files

Debelle_15531800_2024.pdf
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  • 3.72 MB

Details

Supervisors
Macq, Benoît
Faculty
Ecole polytechnique de Louvain
Degree label
Master [120] : ingénieur civil en mathématiques appliquées, à finalité spécialisée
Abstract
Neuropsychological tests are used to assess a person's cognitive functions in order to diagnose dementia, in particular Alzheimer's disease. The aim of this work is to integrate machine learning (ML) and computer vision (CV) into the diagnosis of Alzheimer's disease in order to improve it and enable earlier detection. The focus is on the neuropsychological clock test, and more specifically on the recognition of numbers from 0 to 12. The number recognition model was tested on synthetic data generated from the MNIST set and on real data from clock tests performed by controls and Alzheimer's patients. The results suggest that Alzheimer's disease affects handwriting.