Applications of ANN in COVID-19

Xufu Liu ； Zhengkai Zhu ； Ziguan Yu

《International Core Journal of Engineering》 7卷2期 (2021/02) Pp. 133-140

https://doi.org/10.6919/ICJE.202102_7(2).0017

摘要

Covid-19 has spread all over the world. It not only makes lots of people die but also has a huge negative impact on the economy in the world. In order to resist the Covid-19, many researchers have applied machine learning algorithms to deal with different problems brought by Covid-19. No one has summarized different machine learning algorithms and their applications to the Covid-19. Thus, in order to help people understand the importance of machine learning algorithm in the medical field and principles of some machine learning algorithms. We write this review that covers three different machine learning algorithms, which are Artificial neural network (ANN), Fuzzy neural network (FNN) and Convolutional neural network (CNN), and their applications to the Covid-19 and related fields. In the end, we found that different machine learning algorithms with different merits can be used to deal with many Covid-19 problems such as predicting Covid-19 incidence rate, vaccine design and the diagnosis of Covid-19. To some extend, this review can help researchers find solutions when they met similar virus-related problems.

關鍵字

ANN ； FNN ； CNN ； COVID-19

參考文獻

LeCun, Y.; Bengio, Y.; Hinton, G. Deep learning. Nature 2015, 521, 436–444.

Hassoun, M.H. Fundamentals of Artificial Neural Networks; MIT Press: Cambridge, MA, USA, 1995.

Graupe, D. Principles of Artificial Neural Networks; World Scientific, Publishing Company: Singapore, 2013; Volume 7.

Guresen, E.; Kayakutlu, G.; Daim, T.U. Using artificial neural network models in stock market index prediction. Expert Syst. Appl. 2011, 38, 10389–10397.

Mou, L.; Ghamisi, P.; Zhu, X.X. Deep recurrent neural networks for hyperspectral image classification. IEEE Trans. Geosci. Remote Sens. 2017, 55, 3639–3655.