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Machine Learning Techniques for the Diagnosis of Alzheimer-s Disease:A Review - 2020

Machine Learning Techniques For The Diagnosis Of Alzheimer-S Disease:A Review

Research Area:  Machine Learning


Alzheimer-s disease is an incurable neurodegenerative disease primarily affecting the elderly population. Efficient automated techniques are needed for early diagnosis of Alzheimer-s. Many novel approaches are proposed by researchers for classification of Alzheimer-s disease. However, to develop more efficient learning techniques, better understanding of the work done on Alzheimer-s is needed. Here, we provide a review on 165 papers from 2005 to 2019, using various feature extraction and machine learning techniques. The machine learning techniques are surveyed under three main categories: support vector machine (SVM), artificial neural network (ANN), and deep learning (DL) and ensemble methods. We present a detailed review on these three approaches for Alzheimer-s with possible future directions.


Author(s) Name:  M. Tanveer , B. Richhariya , R. U. Khan , A. H. Rashid , P. Khanna , M. Prasad , C. T. Lin

Journal name:  ACM Transactions on Multimedia Computing, Communications, and Applications

Conferrence name:  

Publisher name:  ACM

DOI:  10.1145/3344998

Volume Information:  Volume 16,Issue 1, Article No.: 30,pp 1–35