Review of Artificial Intelligence-based COVID-19 Detection and A CNN-based Model to Detect Covid-19 from X-Rays and CT images

Abstract

Various diseases are rising in the world in different regions. Each disease is diagnosed through its signs, & symptoms, and is cured accordingly. Some persons have immunity to fight against such diseases, but most of the persons become the victim of these diseases. The epidemic in China triggered by a novel coronavirus (Covid-19) presents an unprecedented danger to general safety, worldwide. Covid-19 has a more rapid transmission rate. A speedy symptomatic standard check to identify the infectious disease is required to prevent its spread. In an existing situation, testing kits of Covid-19 are available in less quantity and they require significant time to produce outcomes. The purpose of this research is to explore recently reported techniques for automated identification of Covid-19 from medical images and to report an efficient method for the detection of Covid-19 from digital X-Ray and computed tomography images. The proposed model can assist in the identification of Covid-19 at its initial level in lesser time. Publically available and locally developed datasets have been used for research and experiments. The highest classification accuracy achieved through the reported model is 99.40%.

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