The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.

IF 6.3 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Mayur Suresh Gawande, Nikita Zade, Praveen Kumar, Swapnil Gundewar, Induni Nayodhara Weerarathna, Prateek Verma
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Abstract

Integrating Artificial Intelligence (AI) across numerous disciplines has transformed the worldwide landscape of pandemic response. This review investigates the multidimensional role of AI in the pandemic, which arises as a global health crisis, and its role in preparedness and responses, ranging from enhanced epidemiological modelling to the acceleration of vaccine development. The confluence of AI technologies has guided us in a new era of data-driven decision-making, revolutionizing our ability to anticipate, mitigate, and treat infectious illnesses. The review begins by discussing the impact of a pandemic on emerging countries worldwide, elaborating on the critical significance of AI in epidemiological modelling, bringing data-driven decision-making, and enabling forecasting, mitigation and response to the pandemic. In epidemiology, AI-driven epidemiological models like SIR (Susceptible-Infectious-Recovered) and SIS (Susceptible-Infectious-Susceptible) are applied to predict the spread of disease, preventing outbreaks and optimising vaccine distribution. The review also demonstrates how Machine Learning (ML) algorithms and predictive analytics improve our knowledge of disease propagation patterns. The collaborative aspect of AI in vaccine discovery and clinical trials of various vaccines is emphasised, focusing on constructing AI-powered surveillance networks. Conclusively, the review presents a comprehensive assessment of how AI impacts epidemiological modelling, builds AI-enabled dynamic models by collaborating ML and Deep Learning (DL) techniques, and develops and implements vaccines and clinical trials. The review also focuses on screening, forecasting, contact tracing and monitoring the virus-causing pandemic. It advocates for sustained research, real-world implications, ethical application and strategic integration of AI technologies to strengthen our collective ability to face and alleviate the effects of global health issues.

人工智能在大流行应对中的作用:从流行病学建模到疫苗开发。
跨多个学科整合人工智能(AI)已经改变了全球大流行应对的格局。本综述调查了人工智能在作为全球卫生危机出现的大流行中的多维作用,以及它在防范和应对中的作用,从加强流行病学建模到加速疫苗开发。人工智能技术的融合引领我们进入了一个数据驱动决策的新时代,彻底改变了我们预测、减轻和治疗传染病的能力。本次审查首先讨论了大流行对全球新兴国家的影响,详细阐述了人工智能在流行病学建模、带来数据驱动的决策以及实现对大流行的预测、缓解和应对方面的关键意义。在流行病学方面,人工智能驱动的流行病学模型,如SIR(易感-感染-恢复)和SIS(易感-感染-易感)被应用于预测疾病的传播、预防疫情和优化疫苗分配。该综述还展示了机器学习(ML)算法和预测分析如何提高我们对疾病传播模式的认识。强调人工智能在疫苗发现和各种疫苗临床试验中的协作方面,重点是构建人工智能监测网络。最后,该综述全面评估了人工智能如何影响流行病学建模,通过协作ML和深度学习(DL)技术构建支持人工智能的动态模型,以及开发和实施疫苗和临床试验。审查还侧重于筛查、预测、接触者追踪和监测引起病毒的大流行。它倡导人工智能技术的持续研究、现实影响、伦理应用和战略整合,以加强我们面对和减轻全球卫生问题影响的集体能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.30
自引率
0.00%
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0
审稿时长
10 weeks
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