Methods for improving accuracy of the dementia diagnosis using feature dimension reduction
DOI:
https://doi.org/10.20535/SRIT.2308-8893.2019.2.03Keywords:
diagnosis Alzheimer’s disease, ensemble learning methods, classification, convolutional neural networkAbstract
In this paper, the problem of choosing the right feature for diagnosing Dementia is discussed. Several features that could affect dementia were reviewed and their importance was evaluated. Random forest algorithm and SVM for the dementia diagnosis have been developed and investigated. Experiments were conducted on the open-source database and compared with the related works’ results. The purpose of the paper is to improve the accuracy of diagnosis of dementia using the reduction of features' dimension. This article is devoted to analysis of the main distinguishing features of Alzheimer`s dementia, applicable methods and treatment of Alzheimer's dementia on early stage that could help to avoid negative consequences connected with progress of the disease. The purpose of the paper is to improve the accuracy of diagnosis of dementia.References
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