{"title":"通过深度学习对 COVID-19 咳嗽音频进行分类的综合评述","authors":"Praveen Gupta, S. Degadwala","doi":"10.32628/cseit2361049","DOIUrl":null,"url":null,"abstract":"This review paper provides a comprehensive analysis of the advancements in COVID-19 cough audio classification through deep learning techniques. With the ongoing global pandemic, there is a growing need for non-intrusive and rapid diagnostic tools, and the utilization of audio-based methods for COVID-19 detection has gained considerable attention. The paper systematically reviews and compares various deep learning models, methodologies, and datasets employed for COVID-19 cough audio classification. The effectiveness, challenges, and future directions of these approaches are discussed, shedding light on the potential of audio-based diagnostics in the context of the current public health crisis.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"83 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Comprehensive Review on COVID-19 Cough Audio Classification through Deep Learning\",\"authors\":\"Praveen Gupta, S. Degadwala\",\"doi\":\"10.32628/cseit2361049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This review paper provides a comprehensive analysis of the advancements in COVID-19 cough audio classification through deep learning techniques. With the ongoing global pandemic, there is a growing need for non-intrusive and rapid diagnostic tools, and the utilization of audio-based methods for COVID-19 detection has gained considerable attention. The paper systematically reviews and compares various deep learning models, methodologies, and datasets employed for COVID-19 cough audio classification. The effectiveness, challenges, and future directions of these approaches are discussed, shedding light on the potential of audio-based diagnostics in the context of the current public health crisis.\",\"PeriodicalId\":313456,\"journal\":{\"name\":\"International Journal of Scientific Research in Computer Science, Engineering and Information Technology\",\"volume\":\"83 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Scientific Research in Computer Science, Engineering and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32628/cseit2361049\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32628/cseit2361049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Comprehensive Review on COVID-19 Cough Audio Classification through Deep Learning
This review paper provides a comprehensive analysis of the advancements in COVID-19 cough audio classification through deep learning techniques. With the ongoing global pandemic, there is a growing need for non-intrusive and rapid diagnostic tools, and the utilization of audio-based methods for COVID-19 detection has gained considerable attention. The paper systematically reviews and compares various deep learning models, methodologies, and datasets employed for COVID-19 cough audio classification. The effectiveness, challenges, and future directions of these approaches are discussed, shedding light on the potential of audio-based diagnostics in the context of the current public health crisis.