Early Detection of COVID-19 by Reptile Search Algorithm-Based Machine Learning Strategy

COVID-19 virus infects the lungs as well as the upper respiratory system. Recently, it has been discovered that images from chest X-rays (CXR) which are helpful for monitoring COVID-19 disease and other lung conditions. This research developed a COVID-19 early detection method based on the reptile search algorithm (RSA) and machine learning (ML) approach to relieve these concerns. In order to rapidly and accurately detect COVID-19 from CXR images, one of the most prevalent types of medical imaging. Pre-processing, feature extraction, feature selection, and classification were the four divisions of this study project. CXR images are gathered and pre-processed to improve the quality. Extract the features to covert binary values that are fed to the ML model to detect the disease. The comparison of performance metrics among ML methods such as accuracy, precision, recall and error have a value of 98%, 96%, 94% and 2%, respectively.