Research Area:  Machine Learning

Abstract:

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.

Keywords:  

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

Publisher name:  ACM

DOI:  10.1145/3344998

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

Paper Link:   https://dl.acm.org/doi/abs/10.1145/3344998