Covid-19 Prediction using Machine Learning Algorithms

Technology advancement has a big impact on every part of life, whether you work in the medical field or any other sector. AI has shown encouraging results in the healthcare industry by utilizing data processing and analysis to guide its decisions. To stop a life-threatening infection from growing an...

Full description

Saved in:

Bibliographic Details
Published in:	2024 2nd International Conference on Computer, Communication and Control (IC4) pp. 1 - 6
Main Authors:	Gaikwad, Deepali K., Gaikwad, Ashok
Format:	Conference Proceeding
Language:	English
Published:	IEEE 08-02-2024
Subjects:	COVID-19 COVID-19 related symptoms Decision Tree Algorithm Logistic Regression Algorithm Machine learning Machine learning algorithms Medical treatment Prediction algorithms Predictive models Random Forest Algorithm Software algorithms
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	Technology advancement has a big impact on every part of life, whether you work in the medical field or any other sector. AI has shown encouraging results in the healthcare industry by utilizing data processing and analysis to guide its decisions. To stop a life-threatening infection from growing and spreading, the most important thing to do is to recognize it early. The new COVID-19 coronavirus is an unseen threat that the entire globe is fighting. It is rapidly and violently spreading throughout the earth. People are becoming infected with the coronavirus, which spreads quickly between individuals. The COVID-19 pandemic's global expansion has grown to be a serious source of concern for the medical community, the requirement for a system that can be utilized to find the infection. As technology continues to progress, researchers are now given access to a multitude of COVID-19-related data that can be used to discover important information about the infection. In this investigation, our examined the COVID-19 prediction accuracy of various machine learning methods and utilized the approach with the highest accuracy for the model ultimate testing.
DOI:	10.1109/IC457434.2024.10486062