基于机器学习和深度学习的疫情前后评估预测分析

Ishaan Walecha, Divya Jain
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摘要

在这个全球紧急时刻,每天都有大量人失去生命,人们正在努力开发解决COVID-19挑战的方法/技术。机器学习(ML)和人工智能(AI)工具以前也被用于大流行时期,它们通过在各个领域提供可靠的结果证明了自己的价值,这就是ML工具被广泛用于抗击这次大流行的原因。本文综述了机器学习在COVID-19后和前条件下的应用,包括接触者追踪、疫苗开发、预测和诊断、风险管理和疫情预测,以帮助医疗保健系统高效工作。本综述讨论了正在进行的关于大流行病毒的研究,其中已将各种ML模型应用于特定数据集,以产生可用于人群中病毒风险或爆发预测、疫苗开发和接触者追踪的输出。因此,机器学习对COVID-19的重要性和贡献是不言自明的,但不应妥协的是基于该分析采用或产生的解决方案/方法/政策的质量和准确性,这将在现实世界中对现实人群产生影响。
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Prediction analysis on the pre and post COVID outbreak assessment using machine learning and deep learning
In this time of a global urgency where people are losing lives each day in a large number, people are trying to develop ways/technology to solve the challenges of COVID-19. Machine learning (ML) and artificial intelligence (AI) tools have been employed previously as well to the times of pandemic where they have proven their worth by providing reliable results in varied fields this is why ML tools are being used extensively to fight this pandemic as well. This review describes the applications of ML in the post and pre COVID-19 conditions for contact tracing, vaccine development, prediction and diagnosis, risk management, and outbreak predictions to help the healthcare system to work efficiently. This review discusses the ongoing research on the pandemic virus where various ML models have been employed to a certain data set to produce outputs that can be used for risk or outbreak prediction of virus in the population, vaccine development, and contact tracing. Thus, the significance and the contribution of ML against COVID-19 are self-explanatory but what should not be compromised is the quality and accuracy based on which solutions/methods/policies adopted or produced from this analysis which will be implied in the real world to real people.
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