Identification of Pneumonia Symptoms in Covid19 patients using Transfer Learning Approach

Abstract

Over 1 million individuals were impacted globally by the COVID 19 epidemic, which also claimed over 10 lakh lives. As a result of the Covid 19 infection, pneumonia might develop, putting the patient in danger of serious illness or even death. Therefore, it is crucial to recognize the signs of pneumonia and its existence in Covid 19 patients. The VGG16 architecture is a Deep Learning architecture that was the first runner-up in the 2014 visual recognition challenge. The researchers are applying transfer-learning to detect the presence of pneumonia in this case. Chest X-ray scans from kaggle, a publicly accessible open dataset, served as the study’s data set. The model’s accuracy was 95.83%, and a comparison with various other models was also presented.