Interactive Automation of COVID-19 Classification through X-Ray Images using Machine Learning

Machine learning had given many benefits to the humankind by implementing technology on the daily human lives. To add, when the pandemic COVID19 hits Earth globally in early 2020, mankind is challenged with the sudden emergence of the virus that costed many lives. With the virus spreading fast, it has become a challenge towards medical experts to keep their environment clean from the virus. Scientists and medical experts raced to find a cure and plausible methods to avoid the virus from spreading, ranging from lockdowns to standard operating procedures on daily routines. Studies have also shown that geographical factors in the rural area becomes a great challenge to experts on providing medical attention towards the community that had been infected in the rural areas. Fortunately, with the help of advanced current technology, scientists and medical experts are able to counter these problems. In this study, an experimental model with an accuracy of 87% is used, and the application to a web server is used via Python and Flask. The accuracy is achieved by adjusting batch sizes and implementing image augmentation using Keras' ImageDataGenerator feature. Therefore, this project focuses on utilizing machine learning to classify COVID-19 patients through X-ray images on a web server, which could further improve the accessibility for humanity to seek for medical attention.