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Discrimination of alcohol dependence based on the convolutional neural network.

ABSTRACT: In this paper, a total of 20 sites of single nucleotide polymorphisms (SNPs) on the serotonin 3 receptor A gene (HTR3A) and B gene (HTR3B) are used for feature fusion with age, education and marital status information, and the grid search-support vector machine (GS-SVM), the convolutional neural network (CNN) and the convolutional neural network combined with long and short-term memory (CNN-LSTM) are used to classify and discriminate between alcohol-dependent patients (AD) and the non-alcohol-dependent control group. The results show that 19 SNPs combined with academic qualifications have the best discrimination effect. In the GS-SVM, the area under the receiver operating characteristic (ROC) curve (AUC) is 0.87, the AUC of CNN-LSTM is 0.88, and the performance of the CNN model is the best, with an AUC of 0.92. This study shows that the CNN model can more accurately discriminate AD than the SVM to treat patients in time.

SUBMITTER: Chen F

PROVIDER: S-EPMC7591038 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Discrimination of alcohol dependence based on the convolutional neural network.

Chen Fangfang F Xiao Meng M Chen Cheng C Chen Chen C Yan Ziwei Z Han Huijie H Zhang Shuailei S Yue Feilong F Gao Rui R Lv Xiaoyi X

PloS one 20201027 10

In this paper, a total of 20 sites of single nucleotide polymorphisms (SNPs) on the serotonin 3 receptor A gene (HTR3A) and B gene (HTR3B) are used for feature fusion with age, education and marital status information, and the grid search-support vector machine (GS-SVM), the convolutional neural network (CNN) and the convolutional neural network combined with long and short-term memory (CNN-LSTM) are used to classify and discriminate between alcohol-dependent patients (AD) and the non-alcohol-de ...[more]

PMID: 33108388

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