CFP last date
20 December 2024
Reseach Article

Covid-19: A Tentative Estimation of Fatality Rates using Random Forest Algorithm

by B.K.Praveen Kumar, Gundamaraju Nithya, K.Santhi Sree
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 176 - Number 23
Year of Publication: 2020
Authors: B.K.Praveen Kumar, Gundamaraju Nithya, K.Santhi Sree
10.5120/ijca2020920197

B.K.Praveen Kumar, Gundamaraju Nithya, K.Santhi Sree . Covid-19: A Tentative Estimation of Fatality Rates using Random Forest Algorithm. International Journal of Computer Applications. 176, 23 ( May 2020), 17-22. DOI=10.5120/ijca2020920197

@article{ 10.5120/ijca2020920197,
author = { B.K.Praveen Kumar, Gundamaraju Nithya, K.Santhi Sree },
title = { Covid-19: A Tentative Estimation of Fatality Rates using Random Forest Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { May 2020 },
volume = { 176 },
number = { 23 },
month = { May },
year = { 2020 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume176/number23/31338-2020920197/ },
doi = { 10.5120/ijca2020920197 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:43:17.752559+05:30
%A B.K.Praveen Kumar
%A Gundamaraju Nithya
%A K.Santhi Sree
%T Covid-19: A Tentative Estimation of Fatality Rates using Random Forest Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 176
%N 23
%P 17-22
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The outbreak of the Corona Virus Disease (COVID-19) previously known as 2019 Novel Corona Virus, are known to belong to a family of viruses namely the ‘Coronaviruses’. These viruses are known to affect both animals and humans. These viruses are responsible for several prevailing infections such as a common cold to life-threatening ailments like Severe Acute Respiratory Syndrome (SARS). COVID-19 is caused by a new virus belonging to this family known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2). This outbreak in December 2019 began in Wuhan, China. The virus spread across 114 countries so rapidly that it has been declared as a “pandemic” by the World Health Organization on 11 March 2020 itself[1] . As of now, there is no cure or vaccination to prevent this infection. The people affected by this virus will have mild to moderate respiratory illness like pneumonia and can recover by receiving supportive care under medical supervision. However, it has been observed that older people and people with a medical history of heart diseases, Diabetes, long-term respiratory diseases, and cancer are more at risk for severe illness. In this paper, the possibility of the death of the Corona infected people by considering the above-mentioned factors is observed. The sample dataset will be analyzed using a machine learning algorithm for this purpose. The goal is to predict the death probability of a patient based on his age and previous medical history with the highest accuracy.

References
  1. https://www.who.int/emergencies/diseases/novelcoronavirus-2019
  2. Zou, Quan & Qu, Kaiyang & Luo, Yamei & Yin, Dehui & Ju, Ying & Tang, Hua. (2018). Predicting Diabetes Mellitus with Machine Learning Techniques. Frontiers in Genetics. 9. 10.3389/fgene.2018.00515.
  3. Hegazy, Osman & Soliman, Omar S. & Abdul Salam, Mustafa. (2013). A Machine Learning Model for Stock Market Prediction. International Journal of Computer Science and Telecommunications. 4. 17-23.
  4. Mohri, Mehryar; Rostamizadeh, Afshin; Talwalkar, Ameet (2012). Foundations of Machine Learning. The MIT Press. ISBN 9780262018258.
  5. C.M. BishopPattern recognition and machine learning,Springer, New York (2006)
  6. T.M. Mitchell,The discipline of machine learning: Carnegie Mellon University,School of Computer Science, Machine Learning Department (2006)
  7. I.H. Witten, E. Frank,Data mining: practical machine learning tools and techniques,Morgan Kaufmann (2005)
  8. Wikipedia contributors. "Machine learning." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 22 Apr. 2020. Web.24 Apr. 2020
  9. Douglas, Pamela K. et al. “Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief.” NeuroImage 56 (2011): 544-553.
  10. L. Breiman. Random forests. Machine Learning, 45(1):5–32, 2001.
  11. https://www.worldometers.info/coronavirus/
Index Terms

Computer Science
Information Sciences

Keywords

Coronavirus SARS-CoV-2 pandemic death rate Machine Learning accuracy.