Review of Alzheimer’s Disease Classification Techniques

Authors

  • Aow Yong Li Yew Faculty of Computing, Universiti Teknologi Malaysia, 81318 Johor Bahru, Johor, Malaysia.
  • Ghazali Sulong Faculty of Computing, Universiti Teknologi Malaysia, 81318 Johor Bahru, Johor, Malaysia. School of Informatics and Applied Mathematics, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia.

Keywords:

Alzheimer’s Disease, Feature Extraction, Feature Selection, Principal Component Analysis, Support Vector Machine,

Abstract

Alzheimer’s disease is a brain degeneration illness. It requires earlier detection in order to improve the quality of life of the patient. Many researchers have studied different computed aided approaches in order to help in the diagnosis of the disease. However, there are few well-known techniques that were used in most of the studies. It is challenging in mild cognitive impairment classification too. Therefore, this paper will review the common used methods and the state-of-art methods in Alzheimer’s disease classification. This helps researchers to identify the suitable methodologies in different stages of classification.

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Published

2017-10-20

How to Cite

Yew, A. Y. L., & Sulong, G. (2017). Review of Alzheimer’s Disease Classification Techniques. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(3-3), 117–123. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2886

Issue

Vol. 9 No. 3-3: Special Issue on Software Engineering I

Section

Articles

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