Supervised Machine Learning Approach to COVID-19 Detection Based on Clinical Data
Open Access
- 24 September 2022
- journal article
- research article
- Published by Academic World Research in Medical Journal of the Islamic Republic Of Iran
- Vol. 36 (1) , 831-837
Abstract
Background: The new coronavirus has been spreading since the beginning of 2020, and many efforts have been made to develop vaccines to help patients recover. It is now clear that the world needs a rapid solution to curb the spread of COVID-19 worldwide with non-clinical approaches such as artificial intelligence techniques. ...Keywords
This publication has 35 references indexed in Scilit:
- Automated detection of COVID-19 cases using deep neural networks with X-ray imagesComputers in Biology and Medicine, 2020
- Using X-ray images and deep learning for automated detection of coronavirus diseaseJournal of Biomolecular Structure and Dynamics, 2020
- The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling studyThe Lancet Public Health, 2020
- The clinical characteristics of pneumonia patients coinfected with 2019 novel coronavirus and influenza virus in Wuhan, ChinaJournal of Medical Virology, 2020
- Re-epithelialization and immune cell behaviour in an ex vivo human skin modelScientific Reports, 2020
- Minimum data set development for a drug poisoning registry systemDigital Health, 2019
- A Systematic Review on Healthcare Analytics: Application and Theoretical Perspective of Data MiningHealthcare, 2018
- Building predictive models for MERS-CoV infections using data mining techniquesJournal of Infection and Public Health, 2016
- The prevention and handling of the missing dataKorean Journal of Anesthesiology, 2013
- Rotation Forest: A New Classifier Ensemble MethodIEEE Transactions on Pattern Analysis and Machine Intelligence, 2006