COVID-19 Detection Using CNN-ResNet-50 Model

ABSTRACT

COVID-19 is a deadly virus that originated in 2019 and could be easily transmitted from one geographical area to another. It affected the integral world, resulting in severe mortality due to its contagious effect on human life. The infection rate is continuously growing and it is becoming unmanageable since the virus moves easily from one human to another. Once we detect the COVID-19 virus in its early stages, we can easily reduce the death rate. The most common and widely used method of diagnosing COVID is through reverse transcription polymerase chain (RT-PCR). But the RT-PCR test is time consuming, inaccurate, and expensive. In this situation, the time period for the detection of viruses is valuable. Keeping these limitations in mind, we use an X-ray image of the chest to identify the COVID-19 infected patient. This procedure is achieved by using convolution neural network (CNN) in deep learning. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.