干旱区生态环境知识资源中心(Arid): Class imbalance learning-driven Alzheimer's detection using hybrid features

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DOI	10.1177/1550147719826048
	Class imbalance learning-driven Alzheimer's detection using hybrid features
	Baik, Ran
通讯作者	Baik, Ran
来源期刊	INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
ISSN	1550-1477
出版年	2019
卷号	15 期号:2
英文摘要	Alzheimer's is the main reason which leads to memory loss of a human being. The living style of an affected person also varies. This variation in the lifestyle creates difficulties for a person to spend a normal life. The detection of Alzheimer's disease in the initial stage accurately has a great significance in the early treatment of the disease. Therefore, it is considered as a challenging task. An efficient method is proposed to detect the Alzheimer's disease in the early stage using magnetic resonance imaging. k-Means clustering is used to develop the proposed method for efficient segmentation of the white matter, cerebrospinal fluid, and grey matter. The amalgam feature vectors are formed using the grey-level co-occurrence matrix and speeded-up robust features based on textural feature extraction. Statistical and histogram of gradients is used from shape-based features. Fisher linear discriminant analysis is used for dimensionality reduction and the resampling method is used to handle the class imbalance problem. The algorithm is evaluated using the three classifiers k-nearest neighbour, support vector machine and random forest. The dataset of OASIS is used to assess the outcomes. The proposed approach achieved the optimum accuracy of 92.7%.
英文关键词	Alzheimer's detection class imbalance learning histogram of gradients Fisher linear discriminant analysis
类型	Article
语种	英语
国家	South Korea
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000458805900001
WOS关键词	MILD COGNITIVE IMPAIRMENT ; FEATURE-RANKING ; DISEASE CLASSIFICATION ; DIAGNOSIS
WOS类目	Computer Science, Information Systems ; Telecommunications
WOS研究方向	Computer Science ; Telecommunications
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/216404
作者单位	Honam Univ, Dept Comp Engn, Convergence Sch ICT, 417 Eodeung Daero, Gwangju 506090, South Korea
推荐引用方式 GB/T 7714	Baik, Ran. Class imbalance learning-driven Alzheimer's detection using hybrid features[J],2019,15(2).
APA	Baik, Ran.(2019).Class imbalance learning-driven Alzheimer's detection using hybrid features.INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS,15(2).
MLA	Baik, Ran."Class imbalance learning-driven Alzheimer's detection using hybrid features".INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 15.2(2019).

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