COVID-19 Patient Health Prediction Using Boosted Random Forest Algorithm
Central South University of Forestry and Technology · Central South University · +6 more institutions
Abstract
Integration of artificial intelligence (AI) techniques in wireless infrastructure, real-time collection, and processing of end-user devices is now in high demand. It is now superlative to use AI to detect and predict pandemics of a colossal nature. The Coronavirus disease 2019 (COVID-19) pandemic, which originated in Wuhan China, has had disastrous effects on the global community and has overburdened advanced healthcare systems throughout the world. Globally; over 4,063,525 confirmed cases and 282,244 deaths have been recorded as of 11th May 2020, according to the European Centre for Disease Prevention and Control agency. However, the current rapid and exponential rise in the number of patients has…
Citation impact
- FWCI
- 47.80
- Percentile
- 100%
- References
- 25
Authors
9- CICelestine IwendiCorresponding
Central South University of Forestry and Technology, Central South University
- AKAli Kashif Bashir
Manchester Metropolitan University
- APAtharva Peshkar
Raisoni Group of Institutions
- RSR. Sujatha
Vellore Institute of Technology University
- JMJyotir Moy Chatterjee
Lord Buddha Education Foundation
Topics & keywords
- Random forest
- Pandemic
- Coronavirus disease 2019 (COVID-19)
- Computer science
- AdaBoost
- Machine learning
- Medicine
- Artificial intelligence