A Review of Alzheimer's Disease Classification Using Neuropsychological Data and Machine Learning

被引：0
|
作者：
Lyu, Gang [1 ,2 ]
机构：
[1] Changshu Inst Technol, Suzhou, Peoples R China
[2] Univ N Carolina, Chapel Hill, NC 27515 USA
来源：
2018 11TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2018) | 2018年
关键词：
Alzheimer's disease; machine learning; feature selection; neuropsychological data; SPEECH; DEMENTIA; LANGUAGE;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
Early detection of Alzheimer's disease (AD) is essential. Compared with manual judgment, using machine learning to recognize AD has the advantages of high efficiency and low cost. After reviewing the research progress in using machine learning technology and neuropsychological data to identify AD, we point out that, firstly, the dataset of AD should be expanded by discussing around a specific topic, secondly, more reasonable features should be automatically selected by machine learning, at last, DNN model for predicting AD should be further study.
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页数：5
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