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Profiling Individuals With Dementia Using Cluster Analysis
Alzheimer's disease has long been present and has affected a significant number of people throughout its history, resulting in a vast amount of data for researchers. Making sense of that amount of data depends on the appropriate data analysis methods and algorithms. The purpose of this study is to profile individuals with dementia by conducting a cluster analysis. A two-stage clustering analysis is employed to group individuals with dementia or without dementia regarding the key features of Alzheimer’s disease. Two-stage clustering analysis firstly enables one to determine the groups of individuals they belong to, and after that, it provides a way to profile individuals with Alzheimer's disease according to the features in the Alzheimer Features dataset. Although a single data exploration analysis is used in this study, its contribution to the literature is quite high because the literature lacks clustering studies conducted on the same dataset features. In further research, it is recommended to use clustering-based classification methods for the same or similar datasets.