A Review on the Detection of the Post COVID-19 Symptoms for Long Term Diseased Patients using Machine Learning Algorithms

Author:

Patibandla Anitha

Abstract

Abstract Long term diseases require continuous monitoring, sometimes periodic monitoring to verify if any serious concern requires an attention. In recent years, it is noticed that the COVID-19 pandemic has triggered serious concern towards the long-term diseased individuals. As the mortality rate of the COVID-19 clearly indicates that the highest percentage of deaths reflect in the individuals suffering from long term diseases such as diabetes, pneumonia, cardiovascular and acute renal failure. Though they are tested for COVID negative through conventional apparatus, it doesn’t confer that they are completely out of post consequences. Hence a periodic, if necessary continuous monitoring needs to be aided, which in current scenario is a challenging task. Hence, our current article reviews the use of machine learning algorithms to detect and diagnose pre and post COVID-19 effects on long term diseased patients.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference38 articles.

1. Application of Machine Learning to Predict Acute Kidney Disease in Patients With Sepsis Associated Acute Kidney Injury;He;Frontiers in Medicine,2021

2. Machine learning-based prediction of COVID-19 diagnosis based on symptoms;Zoabi;npj digital medicine,2021

3. Global variants of COVID-19: Current understanding;Roy;Journal of Biomedical Sciences,2021

4. Improving Classification Performance for Diabetes with Linear Discriminant Analysis and Genetic Algorithm;Alharan

5. Detection of pneumonia in chest Xray images by using 2D discretewavelet feature extraction with random forest;Akgundogdu;International Journal of Imaging Systems and Technology,2021

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3