AI Techniques for COVID-19

IEEE Access. 2020 Jul 8:8:128776-128795. doi: 10.1109/ACCESS.2020.3007939. eCollection 2020.

Abstract

Artificial Intelligence (AI) intent is to facilitate human limits. It is getting a standpoint on human administrations, filled by the growing availability of restorative clinical data and quick progression of insightful strategies. Motivated by the need to highlight the need for employing AI in battling the COVID-19 Crisis, this survey summarizes the current state of AI applications in clinical administrations while battling COVID-19. Furthermore, we highlight the application of Big Data while understanding this virus. We also overview various intelligence techniques and methods that can be applied to various types of medical information-based pandemic. We classify the existing AI techniques in clinical data analysis, including neural systems, classical SVM, and edge significant learning. Also, an emphasis has been made on regions that utilize AI-oriented cloud computing in combating various similar viruses to COVID-19. This survey study is an attempt to benefit medical practitioners and medical researchers in overpowering their faced difficulties while handling COVID-19 big data. The investigated techniques put forth advances in medical data analysis with an exactness of up to 90%. We further end up with a detailed discussion about how AI implementation can be a huge advantage in combating various similar viruses.

Keywords: Big data; artificial intelligence; cloud computing; deep learning; the IoT.

Grants and funding

This work was supported in part by the Research Office of Zayed University, UAE, under Grant R19095 and in part by the Al Ain University, UAE, under Grant ERF-20.