Artificial Intelligence against COVID-19 Pandemic: A Comprehensive Insight

大流行 2019年冠状病毒病(COVID-19) 重症监护医学 肺炎 重新调整用途 严重急性呼吸综合征冠状病毒2型(SARS-CoV-2) 医学 冠状病毒 人工智能 计算机科学 传染病(医学专业) 疾病 病理 生物 生态学 内科学
作者
Azhar Equbal,Sarfaraz Masood,Iftekhar Equbal,S Rehan Ahmad,Noor Zaman Khan,Zahid A. Khan
出处
期刊:Current Medical Imaging Reviews [Bentham Science Publishers]
卷期号:19 (1): 1-18
标识
DOI:10.2174/1573405617666211004115208
摘要

: COVID-19 is a pandemic initially identified in Wuhan, China, which is caused by a novel coronavirus, also recognized as the Severe Acute Respiratory Syndrome (SARS-nCoV-2). Unlike other coronaviruses, this novel pathogen may cause unusual contagious pain, which results in viral pneumonia, serious heart problems, and even death. Researchers worldwide are continuously striving to develop a cure for this highly infectious disease, yet there are no well-defined absolute treatments available at present. Several vaccination drives using emergency use authorisation vaccines have been held across many countries; however, their long-term efficacy and side-effects studies are yet to be studied. Various analytical and statistical models have been developed, however, their outcome rate is prolonged. Thus, modern science stresses the application of state-of-the-art methods to combat COVID-19. This paper aims to provide a deep insight into the comprehensive literature about AI and AI-driven tools in the battle against the COVID-19 pandemic. The high efficacy of these AI systems can be observed in terms of highly accurate results, i.e., > 95%, as reported in various studies. The extensive literature reviewed in this paper is divided into five sections, each describing the application of AI against COVID-19 viz. COVID-19 prevention, diagnostic, infection spread trend prediction, therapeutic and drug repurposing. The application of Artificial Intelligence (AI) and AI-driven tools are proving to be useful in managing and fighting against the COVID-19 pandemic, especially by analysing the X-Ray and CT-Scan imaging data of infected subjects, infection trend predictions, etc.

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