S. Devi, Amirthavarshini D, Anbukani R S, Harini T K
{"title":"A Medical Decision Support System to Detect Covid-19 Pneumonia Using CNN","authors":"S. Devi, Amirthavarshini D, Anbukani R S, Harini T K","doi":"10.1109/i-PACT52855.2021.9696553","DOIUrl":null,"url":null,"abstract":"Due to the pandemic by the spread of the COVID virus, there has been a mandatory demand to screen patients. Predominantly RTPCR test is used to detect the virus. The RTPCR test is the most commonly used technique to detect COVID - 19 viruses. The test takes a minimum of 12 hours which is time-consuming and might put a patient's life at stake. This detection method for COVID screening is said to have a false detection rate. CT scans have been used for COVID-19 screening and using CT has several challenges especially since their radiation dose is considerably higher than x-rays. Hence, CXRs are a better choice for the initial assessment. Detection of COVID-19 pneumonia is a fine-grained problem as doctors cannot detect it just by looking at the x-ray images. Moreover, the radiologists visit many patients every day and the diagnosis process take significant time, which may increase errors in screening notably. Therefore, a medical decision support system for screening COVID-19 patients is of utmost importance. Our proposed system is a web application that helps to screen COVID-19 patients effectively.","PeriodicalId":335956,"journal":{"name":"2021 Innovations in Power and Advanced Computing Technologies (i-PACT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Innovations in Power and Advanced Computing Technologies (i-PACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/i-PACT52855.2021.9696553","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Due to the pandemic by the spread of the COVID virus, there has been a mandatory demand to screen patients. Predominantly RTPCR test is used to detect the virus. The RTPCR test is the most commonly used technique to detect COVID - 19 viruses. The test takes a minimum of 12 hours which is time-consuming and might put a patient's life at stake. This detection method for COVID screening is said to have a false detection rate. CT scans have been used for COVID-19 screening and using CT has several challenges especially since their radiation dose is considerably higher than x-rays. Hence, CXRs are a better choice for the initial assessment. Detection of COVID-19 pneumonia is a fine-grained problem as doctors cannot detect it just by looking at the x-ray images. Moreover, the radiologists visit many patients every day and the diagnosis process take significant time, which may increase errors in screening notably. Therefore, a medical decision support system for screening COVID-19 patients is of utmost importance. Our proposed system is a web application that helps to screen COVID-19 patients effectively.