Modified COVID-19 Indian and international dataset for automatic prediction of risk in an individual using machine learning models using a mobile APP
by Jatin Bindra; Savita Ahlawat; Mohammed Javed
International Journal of Intelligent Engineering Informatics (IJIEI), Vol. 9, No. 2, 2021

Abstract: COVID-19 is a major problem not only impacting the health but also the economic development of countries around the globe. Therefore, automatic COVID-19 diagnosis and risk prediction in an individual is very significant in preventing pandemic and also for proper medication. This paper adopts five machine learning models intended to predict the risk of having COVID-19. The existing datasets- the Indian COVID-19 dataset and the International COVID-19 Dataset have been systematically modified to include negative COVID-19 patient data and also facilitate feature learning. The modified datasets are experimented with models like logistic regression, Naive Bayes, k-nearest neighbours, random forest, and neural network. Further, a comparison is done in these models on the basis of score obtained in prediction on the two datasets. The whole model is also implemented as a Mobile APP to be used in real-time.

Online publication date: Fri, 13-Aug-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
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 Intelligent Engineering Informatics (IJIEI):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your 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