A Comprehensive Survey on the Data-Driven Approaches used for Tackling the COVID-19 Pandemic

Abstract

The current evolution of Artificial Intelligence (AI) is fueled by the massive data sources generated by the Internet of Things (IoT), social media, and a diverse range of mobile and web applications. Machine learning (ML) and deep learning become the key to analyzing these data intelligently and developing complementary intelligent data-driven services in the healthcare sector. The world witnessed many AI-enabled tools that contributed to fighting against the COVID-19 pandemic and accelerated with unprecedented accuracy the development and the deployment of many countermeasures. The main objective of this study is to provide a comprehensive survey on the role of AI and ML methods in the healthcare sector. The study offers cases on how AI/ML can arm the world against future pandemics. Specifically, the study presents all available datasets, the main research problems related to COVID-19, and the solutions that AI and ML technologies offer. Finally, based on the analysis of the current literature, the limitations and open research challenges are highlighted. Our findings show that AI and ML technologies can play an essential role in COVID-19 forecasting, prediction, diagnosis, and analysis. In comparison, most of the previous works did not deploy a comprehensive framework that integrates the ML and DL with network security. This work emphasizes the mandate of including network security in all COVID-19 applications and providing complete and secure healthcare services.