{"title":"COVID-19 Detection using Chest X-RAY","authors":"Jai Shankar K. N., P. G. R., N. C K","doi":"10.46300/9106.2022.16.105","DOIUrl":null,"url":null,"abstract":"In view of the COVID-19 pandemic, the exponential increase in the COVID-19 patients is leading to the enormous demand on the healthcare systems across the world. The allocation of resources towards the detection of the people affected by the virus plays a key role in curbing the pandemic and slowing down the spread of the virus to a greater extent. While traditional procedures are utilized to discover COVID-19 individuals, testing each individual with a limited number of testing kits is a massive undertaking. Most healthcare systems include X-ray equipment, and most of them being digitized, can be utilized as a way of screening for COVID-19 patients. This paper proposes AI model that can analyze and predict a possible COVID-19 patient, which can be used to prioritize the people for further testing. Further we propose the automation of this process where the models can be deployed in a remote server or an edge computing device where the X-ray images can be screened by the deep learning model to give predictions with very less turnaround time.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":"451 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Circuits, Systems and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46300/9106.2022.16.105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
In view of the COVID-19 pandemic, the exponential increase in the COVID-19 patients is leading to the enormous demand on the healthcare systems across the world. The allocation of resources towards the detection of the people affected by the virus plays a key role in curbing the pandemic and slowing down the spread of the virus to a greater extent. While traditional procedures are utilized to discover COVID-19 individuals, testing each individual with a limited number of testing kits is a massive undertaking. Most healthcare systems include X-ray equipment, and most of them being digitized, can be utilized as a way of screening for COVID-19 patients. This paper proposes AI model that can analyze and predict a possible COVID-19 patient, which can be used to prioritize the people for further testing. Further we propose the automation of this process where the models can be deployed in a remote server or an edge computing device where the X-ray images can be screened by the deep learning model to give predictions with very less turnaround time.