Survey of Applications of Neural Networks and Machine Learning to COVID-19 Predictions

R. Segall
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引用次数: 2

Abstract

The purpose of this chapter is to illustrate how artificial intelligence (AI) technologies have been used for COVID-19 detection and analysis. Specifically, the use of neural networks (NN) and machine learning (ML) are described along with which countries are creating these techniques and how these are being used for COVID-19 diagnosis and detection. Illustrations of multi-layer convolutional neural networks (CNN), recurrent neural networks (RNN), and deep neural networks (DNN) are provided to show how these are used for COVID-19 detection and prediction. A summary of big data analytics for COVID-19 and some available COVID-19 open-source data sets and repositories and their characteristics for research and analysis are also provided. An example is also shown for artificial intelligence (AI) and neural network (NN) applications using real-time COVID-19 data.
神经网络和机器学习在COVID-19预测中的应用综述
本章的目的是说明人工智能(AI)技术如何用于COVID-19的检测和分析。具体而言,介绍了神经网络(NN)和机器学习(ML)的使用,以及哪些国家正在开发这些技术,以及如何将这些技术用于COVID-19的诊断和检测。本文提供了多层卷积神经网络(CNN)、循环神经网络(RNN)和深度神经网络(DNN)的示例,以展示如何将它们用于COVID-19检测和预测。总结了新冠肺炎大数据分析和一些现有的新冠肺炎开源数据集和存储库及其特点,供研究分析。还举例说明了人工智能(AI)和神经网络(NN)应用实时COVID-19数据的情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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