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Classification and prediction of Alzheimers disease using multi-layer perceptron - 2020

Classification And Prediction Of Alzheimers Disease Using Multi-Layer Perceptron

Research Area:  Machine Learning


With the changing lifestyle, there is a tremendous increase in the cases of Alzheimers disease. People are not able to pacify their urge of accurate diagnosis till date. The main reason for this increment is the changing lifestyle of todays generation because of which they are not able to meet their daily body requirements schedule which can keep them fit both physically and mentally. From childhood to adolescent to middle age, this carelessness does not show any signs of its glimpses but when a person hits the old age, it becomes prominent. In this paper, we have classified the patients suffering from Alzheimers disease using the National Alzheimers Coordinating Centres (NACCs) database with the help of random forest (RF), support vector machine (SVM), K-nearest neighbour (KNN), linear discriminate analysis (LDA) and neural networks (NN). We also used the multi-layer perceptron (MLP) for classification of MRI data and the outcome signified that it proved to be the most competent approach with 94% accuracy.


Author(s) Name:  Monika Jyotiyana and Nishtha Kesswani

Journal name:  International Journal of Reasoning-based Intelligent Systems

Conferrence name:  

Publisher name:   Inderscience

DOI:  10.1504/IJRIS.2020.111785

Volume Information:  Vol. 12, No. 4