COVID-19 Detection Through Smartphone-recorded Coughs Using Artificial Intelligence: An Analysis of Applicability for Pre-screening COVID-19 Patients in Vietnam

Dinh Son Nguyen, K. T. Dang
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引用次数: 1

Abstract

The Covid-19 pandemic is one of the most serious global health epidemics in recent decades. Its consequences have affected hundreds of millions of people in countries around the world because of the high contagiousness and mortality rate of the virus. Since the fourth wave of Covid-19 infections broke out and spread to many cities and provinces in Vietnam, there were over 10,000 infected cases in the community within two months by the Delta coronavirus variants. Therefore, it is very necessary to have a faster and more effective method to prescreen and isolate infected patients as soon as possible. That is why the paper proposes a method using artificial intelligence techniques to detect covid-19 infected patients based on smartphone-recorded cough sounds. The learning models are built using the publicly available data as COUGHVID and Coswara. An analysis of the applicability of the learning models for prescreening Covid-19 patients in Vietnam is also mentioned in the paper.
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利用人工智能通过智能手机记录咳嗽检测COVID-19:对越南COVID-19患者预筛查的适用性分析
Covid-19大流行是近几十年来最严重的全球卫生流行病之一。由于该病毒的高传染性和高死亡率,其后果影响了世界各国数亿人。自第四波新型冠状病毒感染爆发并蔓延到越南许多省市以来,两个月内社区感染病例超过1万例。因此,尽快有一种更快、更有效的方法对感染患者进行预筛查和隔离是非常必要的。因此,该论文提出了一种利用人工智能技术,以智能手机录制的咳嗽声为基础,检测新冠病毒感染者的方法。学习模型是使用COUGHVID和Coswara等公开可用的数据构建的。本文还分析了学习模型在越南Covid-19患者预筛查中的适用性。
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