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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Vydané v:	Neurocomputing (Amsterdam) Ročník 226; s. 16 - 22
Hlavní autori:	Song, Qin, Zheng, Yu-Jun, Xue, Yu, Sheng, Wei-Guo, Zhao, Mei-Rong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 22.02.2017
Predmet:	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
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