Development of COVID-19 Prediction Models from Chest X-Ray Using Transfer Learning

ABSTRACT

Due to the outbreak of corona virus disease (COVID-19) globally, many countries are facing shortages of testing kits and medical resources. Moreover, the current COVID-19 swab test cannot easily perform due to asymptomatic patients. To assist the medical staff, few studies have proposed to detect and classify COVID-19 cases by analyzing radiological images. In this paper, we aim to develop an alternative method using chest X-ray images to provide an automatic and faster diagnosis. Convolutional neural network models that can detect the presence of COVID-19 and pneumonia infection from chest X-ray images are developed by exploiting transfer learning techniques. Three models were developed for comparison, the models yielded an accuracy of 97.3%, 98.2%, and 97.3% respectively. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.