An IoT and artificial intelligence-based patient care system focused on COVID-19 pandemic Online publication date: Mon, 10-Jan-2022
by Vishal Kumar Goar; Nagendra Singh Yadav; Chiranji Lal Chowdhary; Kumaresan P; Mohit Mittal
International Journal of Networking and Virtual Organisations (IJNVO), Vol. 25, No. 3/4, 2021
Abstract: World Health Organization has declared COVID-19 a pandemic. Like many other epidemic outbreaks, the COVID-19 pandemic also faces significant challenges. The digital technology allowed healthcare professionals in identification and isolation to the source of the infection to prevent community transmission of the virus by remotely monitoring the COVID-19 infected patients. We proposed a prediction model using Orange Canvas Program by creating a local instance dataset of eight suspected individuals' measured body parameters. Furthermore, six machine learning classifiers such as KNN, DT, SVM, random forest, neural network and naive Bayes are implemented to train the model on the dataset and in predicting the COVID-19. The results show that the proposed machine learning model successfully detects COVID-19. The evaluation results show that the highest accuracy value is obtained with neural networks and SVM, however neural networks outperform in other statistical parameters besides the accuracy rate.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Networking and Virtual Organisations (IJNVO):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com