Multi-classification machine learning for diagnosing COVID-19 in X-ray

Main Article Content

Mayada Jabbar Kelain

Abstract

The dangerous COVID-19 virus is a threat to all human beings around the world. Effective identification of COVID-19 using advanced machine learning methods is a timely need. Although many complex methods have been proposed in the recent past, they still struggle to achieve the expected performance in classifying and identifying COVID-19 patients using chest X-rays. In addition, most of them are involved in the complex pretreatment task, which is often difficult for a virologist. Meanwhile, deep networks are comprehensive and have shown promising results in image recognition tasks over the past decade. In this work, chest x-ray images were used after processing the images using filters, as well as determining the infection with the virus and its classification by the SVM algorithm, as the algorithm gave good and effective results in knowing the person infected with corona or not

Article Details

How to Cite
Mayada Jabbar Kelain. (2023). Multi-classification machine learning for diagnosing COVID-19 in X-ray. Eurasian Journal of Engineering and Technology, 15, 13–16. Retrieved from https://geniusjournals.org/index.php/ejet/article/view/3340
Section
Articles