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用于计算与COVID-19相关风险因素的多层神经网络设计

Multilayer Neural Network Design for the Calculation of Risk Factor Associated with COVID-19.

作者信息

Chaudhary Anshu, Sharma Manisha

机构信息

Department of Mathematics, Panjab University, Chandigarh, India.

出版信息

Augment Hum Res. 2021;6(1):6. doi: 10.1007/s41133-021-00044-4. Epub 2021 Mar 9.

DOI:10.1007/s41133-021-00044-4
PMID:40477219
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7941404/
Abstract

Coronavirus disease 2019 (COVID-19) is a public health emergency and is of international concern. Till now, there is no effective pharmaceutical treatment available for this disease. This paper presents a multilayer neural network algorithm to calculate the risk factor of getting COVID-19 to the individual based on the symptoms described by World Health Organization. The aim of this study is to provide an approximate risk factor of getting COVID-19 to an individual that helps for further treatment.

摘要

2019冠状病毒病（COVID-19）是突发公共卫生事件，受到国际关注。目前，针对该疾病尚无有效的药物治疗方法。本文提出了一种多层神经网络算法，可根据世界卫生组织描述的症状计算个体感染COVID-19的风险因素。本研究的目的是为个体提供感染COVID-19的近似风险因素，以辅助进一步治疗。

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