An evolutionary deep neural network for predicting morbidity of gastrointestinal infections by food contamination

A majority of gastrointestinal infectious diseases are caused by food contamination, and prediction of morbidity can be very useful for etiological factor controlling and medical resource utilization. However, an accurate prediction is often very difficult not only because there are various types of...

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Bibliographic Details

Published in:	Neurocomputing (Amsterdam) Vol. 226; pp. 16 - 22
Main Authors:	Song, Qin, Zheng, Yu-Jun, Xue, Yu, Sheng, Wei-Guo, Zhao, Mei-Rong
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 22.02.2017
Subjects:	Deep denoising autoencoder (DDAE) Evolutionary algorithms (EAs) Gastrointestinal infections Morbidity prediction Neural networks Deep denoising autoencoder (DDAE) Evolutionary algorithms (EAs) Neural networks Morbidity prediction Gastrointestinal infections
ISSN:	0925-2312, 1872-8286
Online Access:	Get full text
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