Nitin Rajesh, Vysakh Thachileth Poulose, P.L. Umesh, Renu Mary Daniel
{"title":"Comorbidity Based Risk Prediction System for ARDS in COVID-19 Patients","authors":"Nitin Rajesh, Vysakh Thachileth Poulose, P.L. Umesh, Renu Mary Daniel","doi":"10.1109/ICACC-202152719.2021.9708206","DOIUrl":null,"url":null,"abstract":"The Coronavirus disease is an acute respiratory disease that has been designated as a pandemic by the WHO(World Health Organization).The rapid increase in the number of illnesses and death rates has put enormous strain on public health services. Hence, its critical to recognize the comorbidities in COVID-19 patients that led to ARDS(Acute Respiratory Distress Syndrome). In this paper, we use machine learning and deep learning methods to classify high risk COVID-19 patients with accurate results. This paper might speed up decisions made in public health services for predicting medical resources as well as early classification of high risk COVID-19 patients.","PeriodicalId":198810,"journal":{"name":"2021 International Conference on Advances in Computing and Communications (ICACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Advances in Computing and Communications (ICACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACC-202152719.2021.9708206","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
The Coronavirus disease is an acute respiratory disease that has been designated as a pandemic by the WHO(World Health Organization).The rapid increase in the number of illnesses and death rates has put enormous strain on public health services. Hence, its critical to recognize the comorbidities in COVID-19 patients that led to ARDS(Acute Respiratory Distress Syndrome). In this paper, we use machine learning and deep learning methods to classify high risk COVID-19 patients with accurate results. This paper might speed up decisions made in public health services for predicting medical resources as well as early classification of high risk COVID-19 patients.