Recent Trends of Addressing COVID-19 Disease by AI/ML

Abstract

A new hype known as the novel coronavirus has consumed many human lives over the past few years. Consequently, the continued pandemic crisis will necessitate the use of an automated system. The computerised system should be able to provide constant monitoring of different domains of the COVID-19 disease. This study has concentrated on heterogeneous fields of COVID-19 including suspected-infected-recovered-deceased count analysis, impact of lockdown, different health habits responsible for this disease, analysis perforation patterns of lungs due to COVID-19, vaccination intake, and progress investigation. The literature included in this study has been investigated in terms of their prediction efficiency and possible improvements. Due to the exhaustive discourse of current COVID-19 based literature, the study is able to provide a comprehensive knowledge of the ongoing research trends. A concrete future perspective regarding each of the aforementioned domains has been included in the conclusion section which can effectively assist in finding the shortcomings of the existing research.