Multiclass recognition of Alzheimer’s and Parkinson’s disease using various machine learning techniques: A study
作者机构：Department of ECE Channabasaveshwara Institute of Technology TumkurKarnatakaIndia Visvesvaraya Technological University BelagaviKarnatakaIndia
出 版 物：《International Journal of Modeling, Simulation, and Scientific Computing》 (建模、仿真和科学计算国际期刊（英文）)
年 卷 期：2022年第13卷第1期
页 面：235-250页
核心收录：
主 题：Electroencephalograph support vector machine Alzheimer’s disease control normal machine learning
摘 要：The aging population is primarily affected by Alzheimer’s disease(AD)that is an incur-able neurodegenerative *** is a need for an automated efficient technique to diagnose Alzheimer’s in its early *** techniques are used to diagnose *** and neuroimaging methodologies are widely used to highlight changes in the electrical activity of the brain signals that are helpful for early ***’s disease(PD)is a major neurological disease that results in an average of 50,000 new clinical diagnoses worldwide every *** voice features are majorly used as the main means to diag-nose *** major symptoms of PD are loss of intensity,the monotony of loudness and pitch,reduction in stress,unidentified silences,and *** though various innovative models are proposed by explorers about Alzheimer’s and Parkinson’s classifi-cation diseases,still there is a need for efficient learning methodologies and *** paper provides a review on using machine learning(ML)together with several fea-ture extraction techniques that is helpful in the early detection of AD with Parkinson’*** novelty and objective of this study are that the CAD technique is used to improve the accuracy of early diagnosis of *** proposed technique depends on the nonlinear process for data dimension reduction,feature removal,and classification using kernel-based support vector machine(SVM)*** dimension of the input space is radically diminished with kernel *** the learning set is labeled,it creates sense to utilize this information to make a dependable method of dropping the input space *** different techniques of ML are explained under the major approaches ***,artificial neural network(ANN),deep learning(DL),and ensemble methods.A comprehensive assessment is presented at SVM,ANN,and DL approaches for better detection of Alzheimer’s with PD highlighting future insights.
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