A Review on the Detection of the Novel Coronavirus Using Machine Learning Techniques

The novel Coronavirus which has emerged in late 2019 has impacted the lives of the people around the world and has raised new questions in the healthcare sector. There has been extensive research in the area of COVID-19 detection considering its effect on people’s lives everywhere on the planet. The disease has indicated an intensive need for study in the area of Biomedical image processing by the utilisation of Artificial Intelligence and Machine learning strategies. The utmost affected parts in the human body are the lungs. Although RTPCR test can specify whether an individual has Covid or not, it is not a reliable technique since it has low sensitivity and depends on the operator. CT scan of the lungs reveal the exact information about the intensity of the disease in most of the cases and has proved to be reliable. Large datasets are available for carrying out research by using CT scan Imagery. This paper presents an overview of the various methodologies used by various authors in the detection of COVID-19. Application of different Machine learning techniques for the dataset of CT images is proposed and performance metrics will be evaluated in the proposed work.