Machine Learning for COVID-19 Image Analysis
Mahesh Shivling Sadavarte , Dr. V.M.Deshmukh
DOI : 10.46335/IJIES.2023.8.5.11
Abstract— COVID-19 is a worldwide epidemic, as announced by the World Health Organization (WHO) in March 2020. Image Processing methods can play vital roles in identifying COVID-19 patients by visually analyzing their chest x-ray images. As the cost and required time of conventional RT-PCR tests to detect COVID-19, researchers are trying to use medical images like X-Ray and Computed Tomography (CT) images to detect it with the help of Artificial Intelligence (AI) based systems. In this paper, we analyze different classification methodslike GLCM and Gabor features. Performance of SVM, KNN and Naïve Bayes emerging AI-based models that can detect COVID-19 from medical images using X-Ray or CT of lung images. We clant COVID images ssified by usng datasets, preprocessing techniques, segmentation, feature extraction, classification and experimental results which can be helpful for finding future research directions in the domain of automatic diagnosis of Covid-19 disease using Machine learning,
