Machine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions

• Main Authors: Tarik Alafif, Abdul Muneeim Tehame, Saleh Bajaba, Ahmed Barnawi, Saad Zia
• Format: Article
• Language: English
• Published: MDPI AG 2021-01-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: COVID-19; diagnosis; treatment; artificial intelligence; machine learning; deep learning
• Online Access: https://www.mdpi.com/1660-4601/18/3/1117
• ISSN: 1661-7827; 1660-4601

With many successful stories, machine learning (ML) and deep learning (DL) have been widely used in our everyday lives in a number of ways. They have also been instrumental in tackling the outbreak of Coronavirus (COVID-19), which has been happening around the world. The SARS-CoV-2 virus-induced COVID-19 epidemic has spread rapidly across the world, leading to international outbreaks. The COVID-19 fight to curb the spread of the disease involves most states, companies, and scientific research institutions. In this research, we look at the Artificial Intelligence (AI)-based ML and DL methods for COVID-19 diagnosis and treatment. Furthermore, in the battle against COVID-19, we summarize the AI-based ML and DL methods and the available datasets, tools, and performance. This survey offers a detailed overview of the existing state-of-the-art methodologies for ML and DL researchers and the wider health community with descriptions of how ML and DL and data can improve the status of COVID-19, and more studies in order to avoid the outbreak of COVID-19. Details of challenges and future directions are also provided.