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In 2019, the world witnessed a rapid spread of the Coronavirus (COVID-19) disease in one of China's cities, Wuhan. The disease was announced in December 2019 to be a springboard for the whole world, where most countries were infected with it. It greatly affected the health of society and became a real danger to humans. Therefore, it is necessary to diagnose the infected people and quarantine them to combat this pandemic and limit its spread. This paper aims to give a review of COVID-19 diagnosis methods. According to the diagnostic methods, the previous works are classified into two categories for diagnosing Coronavirus; X-ray and Computed Tomography (CT)-Scan. Artificial intelligence (AI) is used to improve the diagnosis accuracy of the presented methods. On this basis, automated diagnostic tools have been developed that distinguish people infected with the Coronavirus from other diseases. Moreover, the performance parameters of the previous studies were compared in terms of diagnosis method, adopted algorithm, diagnosis accuracy, sensitivity, and specificity. Furthermore, the challenges and limitations of the existing methods for diagnosing Coronavirus were explored. AI has proven to be a reliable way to diagnose the spread of the epidemic through advanced algorithms based on blind and machine learning, especially the convolutional neural network (CNN), which plays a vital role in extracting sensitivity, specificity, and accuracy. [ABSTRACT FROM AUTHOR]