Affiliations 

  • 1 Business Information Technology, College of Administration and Economics, University of Sulaimani, Sulaimaniya, Iraq
  • 2 College of Education, Physics Department, Salahaddin University, Shaqlawa, Iraq
  • 3 Electronics and Communication Department, Yildiz Technical University, Istanbul, Turkey
Appl Nanosci, 2023;13(3):2013-2025.
PMID: 34036034 DOI: 10.1007/s13204-021-01868-7

Abstract

Today world thinks about coronavirus disease that which means all even this pandemic disease is not unique. The purpose of this study is to detect the role of machine-learning applications and algorithms in investigating and various purposes that deals with COVID-19. Review of the studies that had been published during 2020 and were related to this topic by seeking in Science Direct, Springer, Hindawi, and MDPI using COVID-19, machine learning, supervised learning, and unsupervised learning as keywords. The total articles obtained were 16,306 overall but after limitation; only 14 researches of these articles were included in this study. Our findings show that machine learning can produce an important role in COVID-19 investigations, prediction, and discrimination. In conclusion, machine learning can be involved in the health provider programs and plans to assess and triage the COVID-19 cases. Supervised learning showed better results than other Unsupervised learning algorithms by having 92.9% testing accuracy. In the future recurrent supervised learning can be utilized for superior accuracy.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.