MACHINE LEARNING FRAMEWORK FOR COVID-19 DIAGNOSIS

IF 2.2 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Data Pub Date : 2021-04-05 DOI:10.1145/3460620.3460624
Sravan kiran Vangipuram, Rajesh Appusamy
{"title":"MACHINE LEARNING FRAMEWORK FOR COVID-19 DIAGNOSIS","authors":"Sravan kiran Vangipuram, Rajesh Appusamy","doi":"10.1145/3460620.3460624","DOIUrl":null,"url":null,"abstract":"With the alarming global health crisis and pandemic, the entire medical industry and every human in this world are desperately looking for new technologies and solutions to monitor and contain the spread of this COVID-19 virus through early detection of its presence among infected patients. The early diagnosis of COVID-19 is hence critical for prevention and limiting this pandemic before it engulfs the humanity. With early diagnosis, the patient may be suggested for self-isolation (or) quarantine under medical supervision. Early detection of COVID-19 can save the patient and minimize the risk of falling prey to CoviD-19. Machine learning, a subset field of Artificial Intelligence can provide a viable solution for early diagnosis of disease and facilitate continuous monitoring of infected patients. AI based approaches can provide a view of the degree of disease severity. In general, Artificial intelligence (AI) could be a better technique for quantitative evaluation of the disease to obtain fruitful results. This paper throws light on the emerging need for AI powered solutions to foster early diagnosis of COVID-19 and suggest an ML based health monitoring framework for diagnosis of infected patients.","PeriodicalId":36824,"journal":{"name":"Data","volume":"5 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2021-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1145/3460620.3460624","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 5

Abstract

With the alarming global health crisis and pandemic, the entire medical industry and every human in this world are desperately looking for new technologies and solutions to monitor and contain the spread of this COVID-19 virus through early detection of its presence among infected patients. The early diagnosis of COVID-19 is hence critical for prevention and limiting this pandemic before it engulfs the humanity. With early diagnosis, the patient may be suggested for self-isolation (or) quarantine under medical supervision. Early detection of COVID-19 can save the patient and minimize the risk of falling prey to CoviD-19. Machine learning, a subset field of Artificial Intelligence can provide a viable solution for early diagnosis of disease and facilitate continuous monitoring of infected patients. AI based approaches can provide a view of the degree of disease severity. In general, Artificial intelligence (AI) could be a better technique for quantitative evaluation of the disease to obtain fruitful results. This paper throws light on the emerging need for AI powered solutions to foster early diagnosis of COVID-19 and suggest an ML based health monitoring framework for diagnosis of infected patients.
COVID-19诊断的机器学习框架
随着令人担忧的全球卫生危机和大流行,整个医疗行业和世界上的每个人都在拼命寻找新的技术和解决方案,通过在感染患者中早期发现COVID-19病毒的存在来监测和控制这种病毒的传播。因此,COVID-19的早期诊断对于预防和在其吞噬人类之前限制这一大流行至关重要。及早诊断,建议自我隔离(或隔离),接受医学监督。及早发现COVID-19可以挽救患者的生命,并将感染COVID-19的风险降至最低。机器学习是人工智能的一个子集,可以为疾病的早期诊断提供可行的解决方案,并促进对感染患者的持续监测。基于人工智能的方法可以提供疾病严重程度的视图。总的来说,人工智能(AI)可能是一种更好的定量评估疾病的技术,以获得丰硕的成果。本文阐明了对人工智能驱动的解决方案的新需求,以促进COVID-19的早期诊断,并提出了一个基于机器学习的健康监测框架,用于诊断感染患者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Data
Data Decision Sciences-Information Systems and Management
CiteScore
4.30
自引率
3.80%
发文量
0
审稿时长
10 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信