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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 12, ISSUE 9, SEPTEMBER 2023

The Impact of Machine Learning in COVID-19 Detection and Diagnosis

Dr. Santosh Jagtap

DOI: 10.17148/IJARCCE.2023.12922

Abstract: Machine learning models for COVID-19 detection using chest X-ray images are important because they are fast, accurate, non-invasive, and accessible. They can be used to identify patients who are at high risk of complications, monitor the progression of the disease, and develop new diagnostic and treatment strategies. The ultimate goal of the research is to develop an accurate, reliable, and cost-effective automated diagnostic tool for COVID-19 detection using CXR images, which can help to reduce the spread of the disease and improve patient outcomes. In this study, the researcher invented a new system for COVID-19 detection based on image processing with chest X-ray images. The primary focus of the experiment is to detect various diseases using chest X-ray images.

Keywords: KNN, RF, NN Works Cited: Dr. Santosh Jagtap " The Impact of Machine Learning in COVID-19 Detection and Diagnosis ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 9, pp. 126-131, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.12922

How to Cite:

[1] Dr. Santosh Jagtap, “The Impact of Machine Learning in COVID-19 Detection and Diagnosis,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.12922