人工智能
2019年冠状病毒病(COVID-19)
机器学习
计算机科学
困境
背景(考古学)
严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)
实施
人工智能应用
医学
疾病
传染病(医学专业)
软件工程
认识论
病理
古生物学
生物
哲学
标识
DOI:10.1080/03091902.2024.2321846
摘要
Researchers and scientists can use computational-based models to turn linked data into useful information, aiding in disease diagnosis, examination, and viral containment due to recent artificial intelligence and machine learning breakthroughs. In this paper, we extensively study the role of artificial intelligence and machine learning in delivering efficient responses to the COVID-19 pandemic almost four years after its start. In this regard, we examine a large number of critical studies conducted by various academic and research communities from multiple disciplines, as well as practical implementations of artificial intelligence algorithms that suggest potential solutions in investigating different COVID-19 decision-making scenarios. We identify numerous areas where artificial intelligence and machine learning can impact this context, including diagnosis (using chest X-ray imaging and CT imaging), severity, tracking, treatment, and the drug industry. Furthermore, we analyse the dilemma's limits, restrictions, and hazards.
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