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Alcoholism Detection by Data Augmentation and Convolutional Neural Network with Stochastic Pooling
Wang, Shui-Hua1,2; Lv, Yi-Ding3; Sui, Yuxiu3; Liu, Shuai4; Wang, Su-Jing5; Zhang, Yu-Dong1; Shuai Liu; Su-Jing Wang; Yu-Dong Zhang
2018
Source PublicationJOURNAL OF MEDICAL SYSTEMS
Correspondent Emailcs_liushuai@imu.edu.cn ; wangsujing@psych.ac.cn ; yudongzhang@ieee.org
ISSN0148-5598
SubtypeArticle
Volume42Issue:1Pages:1-11
Contribution Rank5
Abstract

Alcohol use disorder (AUD) is an important brain disease. It alters the brain structure. Recently, scholars tend to use computer vision based techniques to detect AUD. We collected 235 subjects, 114 alcoholic and 121 non-alcoholic. Among the 235 image, 100 images were used as training set, and data augmentation method was used. The rest 135 images were used as test set. Further, we chose the latest powerful technique-convolutional neural network (CNN) based on convolutional layer, rectified linear unit layer, pooling layer, fully connected layer, and softmax layer. We also compared three different pooling techniques: max pooling, average pooling, and stochastic pooling. The results showed that our method achieved a sensitivity of 96.88%, a specificity of 97.18%, and an accuracy of 97.04%. Our method was better than three state-of-the-art approaches. Besides, stochastic pooling performed better than other max pooling and average pooling. We validated CNN with five convolution layers and two fully connected layers performed the best. The GPU yielded a 149x acceleration in training and a 166x acceleration in test, compared to CPU.

KeywordAlcohol use disorder Data augmentation Convolutional neural network Max pooling Average pooling Stochastic pooling Graphical processing unit
DOI10.1007/s10916-017-0845-x
Indexed BySCI
Language英语
Funding OrganizationNatural Science Foundation of China(61602250) ; Natural Science Foundation of Jiangsu Province(BK20150983)
WOS Research AreaHealth Care Sciences & Services ; Medical Informatics
WOS SubjectHealth Care Sciences & Services ; Medical Informatics
WOS IDWOS:000422690300002
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
WOS KeywordCLASSIFICATION ; TIME
Citation statistics
Cited Times:28[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/26027
Collection中国科学院行为科学重点实验室
Corresponding AuthorShuai Liu; Su-Jing Wang; Yu-Dong Zhang
Affiliation1.Univ Leicester, Dept Informat, Leicester LE1 7RH, Leics, England
2.Nanjing Univ, Sch Elect Sci & Engn, Nanjing 210046, Jiangsu, Peoples R China
3.Nanjing Med Univ, Nanjing Brain Hosp, Dept Psychiat, Nanjing 210029, Jiangsu, Peoples R China
4.Inner Mongolia Univ, Coll Comp Sci, Hohhot 010012, Peoples R China
5.Chinese Acad Sci, Inst Psychol, Key Lab Behav Sci, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Wang, Shui-Hua,Lv, Yi-Ding,Sui, Yuxiu,et al. Alcoholism Detection by Data Augmentation and Convolutional Neural Network with Stochastic Pooling[J]. JOURNAL OF MEDICAL SYSTEMS,2018,42(1):1-11.
APA Wang, Shui-Hua.,Lv, Yi-Ding.,Sui, Yuxiu.,Liu, Shuai.,Wang, Su-Jing.,...&Yu-Dong Zhang.(2018).Alcoholism Detection by Data Augmentation and Convolutional Neural Network with Stochastic Pooling.JOURNAL OF MEDICAL SYSTEMS,42(1),1-11.
MLA Wang, Shui-Hua,et al."Alcoholism Detection by Data Augmentation and Convolutional Neural Network with Stochastic Pooling".JOURNAL OF MEDICAL SYSTEMS 42.1(2018):1-11.
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