The impact of using Convolutional Neural Networks in COVID-19 tasks: A Survey

Abstract

Artificial Intelligence (AI) is considered a robust tool that is widely used in different computer tasks. Machine Learning (ML) as an essential type of AI and deep learning (DL) is merely a branch of (ML). DL can mainly be helping to fast analysis of the medical images, especially the complex images, and this can speed up an early diagnosis of diseases. The Covid-19 pandemic has spread rapidly within societies, creating real panic for all people. Convolutional Neural Network (CNN) is a sub-class of DL which is used to classify medical images. Researchers have exploited the merits of CNNs to deal with COVID-19. This merits and diversity enabled researchers and workers in this field to devise new methods used to detect early cases, predict patients, diagnose patients, design vaccines and drugs and others. This paper aims to conduct a comprehensive survey of the previous works that used CNNs to implement different tasks associated to Covid-19 in order to enrich researchers and provide sufficient information for new works in the same field.