Multimodal Data Integration for Early Alzheimer’s Detection Using Random Forest and Support Vector Machines
Muhammad Nadeem,
Wei Zhang,
Sarwat Aslam
et al.
Abstract:Alzheimer's is a very challenging brain disease to recognize, diagnose, and treat correctly when it appears in its earliest forms. The primary contribution of this research study is about machine learning models, techniques, and approaches. In contrast, Random Forest and Support Vector Machine (SVM) are particularly suitable for identifying and staging Alzheimer's disease stages using multimodal data sources. In this paper, the aim was to develop well-performing predictive models to help diagnose Alzheimer's d… Show more
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