利用咳嗽声检测Covid-19

H. Taneja, A. Abhinav, Apoorv Apoorv, Himanshu Mangal, Naman Agarwal
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引用次数: 1

摘要

由于冠状病毒的大流行,大约有400万人丧生,而且还在继续。许多科学家和研究人员正在努力寻找尽快在人体内检测冠状病毒的方法,以便他们能够尽快开始药物治疗和预防措施。但是,由于实验室设施不足,RT-PCR需要3天以上的时间才能得出结果,而且患者的病情严重,生命受到威胁。所以在这篇论文中,我们提出了一种基于音频的冠状病毒检测技术,我们可以在几分钟内得到结果。冠状病毒是一种呼吸道疾病,呼吸时产生的声音可以告诉我们冠状病毒的存在。基于音频的检测已经被用于哮喘、肺炎的检测。因此,在本文中,我们实现了机器学习和深度学习技术的结合来发现Covid-19的存在,该模型的准确率为78%,f1得分为74%。这项技术可以作为音频数据诊断疾病和拯救生命的起点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of Covid-19 using Cough Sounds
Coronavirus, the pandemic due to which about 4 million have lost their lives and counting, is still on. Many scientists and researchers are trying to find ways to detect coronavirus as soon as possible in the human body so that they can start their medication and precaution as soon as possible. Still, due to lack of lab facilities, the RT-PCR is taking more than three days to give the report, and in the meanwhile, patients get serious and life in danger. So in this paper, we proposed an audio-based coronavirus detection technique in which we can get results in minutes. Coronavirus is a respiratory disease, and the sound produced while breathing can tell us about the presence of coronavirus. Audio-based detection was already used for the detection of asthma, pneumonia. So, in this paper, we implemented a combination of machine learning and deep learning techniques to find the presence of Covid-19, and the model has an accuracy of 78% and an f1 score of 74%. This technique can be used as a starting point for just audio data to diagnose diseases and save lives.
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