Abstract

COVID-19 is an extremely deadly disease which has wreaked havoc worldwide. Initially, the first case was reported in the wet markets of Wuhan, China in the early 2020's. Though the mortality rate is low compared to other dangerous diseases, a lot of people have already succumbed to this virus. Vaccines have been successfully rolled out and it seems effective in preventing the severe symptoms of the coronavirus. However, a section of people (the elderly and people with existing comorbidities) still continue to die. It is extremely important to predict the patient vulnerability using machine learning since appropriate medicines and treatments can be given in time and precious lives can be saved. In this research, the deep forest classifier is utilized to predict the COVID-19 casualty status. This classifier requires extremely low hyperparameter tuning and can easily compete with the deep learning classifiers. This algorithm performed better than the traditional machine learning classifiers with an accuracy of 92%. The positive results obtained signifies the potential use of deep forest to prevent unwanted COVID-19 deaths by effectively deploying them in various medical facilities. Further, it can reduce the extreme burden already existing on healthcare systems caused by the novel coronavirus.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages245-250
Number of pages6
ISBN (Electronic)9781665487160
DOIs
Publication statusPublished - 2022
Event6th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2022 - Shivamogga, India
Duration: 14-10-202215-10-2022

Publication series

Name2022 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2022 - Proceedings

Conference

Conference6th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2022
Country/TerritoryIndia
CityShivamogga
Period14-10-2215-10-22

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Control and Optimization

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