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人工智能在新冠疫情期间的创新应用。

Innovative applications of artificial intelligence during the COVID-19 pandemic.

作者信息

Lv Chenrui, Guo Wenqiang, Yin Xinyi, Liu Liu, Huang Xinlei, Li Shimin, Zhang Li

机构信息

Huazhong Agricultural University, Wuhan 430070, China.

National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research, Shanghai 200001, China.

出版信息

Infect Med (Beijing). 2024 Feb 21;3(1):100095. doi: 10.1016/j.imj.2024.100095. eCollection 2024 Mar.


DOI:10.1016/j.imj.2024.100095
PMID:38586543
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10998276/
Abstract

The COVID-19 pandemic has created unprecedented challenges worldwide. Artificial intelligence (AI) technologies hold tremendous potential for tackling key aspects of pandemic management and response. In the present review, we discuss the tremendous possibilities of AI technology in addressing the global challenges posed by the COVID-19 pandemic. First, we outline the multiple impacts of the current pandemic on public health, the economy, and society. Next, we focus on the innovative applications of advanced AI technologies in key areas such as COVID-19 prediction, detection, control, and drug discovery for treatment. Specifically, AI-based predictive analytics models can use clinical, epidemiological, and omics data to forecast disease spread and patient outcomes. Additionally, deep neural networks enable rapid diagnosis through medical imaging. Intelligent systems can support risk assessment, decision-making, and social sensing, thereby improving epidemic control and public health policies. Furthermore, high-throughput virtual screening enables AI to accelerate the identification of therapeutic drug candidates and opportunities for drug repurposing. Finally, we discuss future research directions for AI technology in combating COVID-19, emphasizing the importance of interdisciplinary collaboration. Though promising, barriers related to model generalization, data quality, infrastructure readiness, and ethical risks must be addressed to fully translate these innovations into real-world impacts. Multidisciplinary collaboration engaging diverse expertise and stakeholders is imperative for developing robust, responsible, and human-centered AI solutions against COVID-19 and future public health emergencies.

摘要

新冠疫情在全球范围内带来了前所未有的挑战。人工智能(AI)技术在应对疫情管理和应对的关键方面具有巨大潜力。在本综述中,我们讨论了人工智能技术在应对新冠疫情带来的全球挑战方面的巨大可能性。首先,我们概述了当前疫情对公共卫生、经济和社会的多重影响。接下来,我们重点关注先进人工智能技术在新冠预测、检测、控制和治疗药物发现等关键领域的创新应用。具体而言,基于人工智能的预测分析模型可以利用临床、流行病学和组学数据来预测疾病传播和患者预后。此外,深度神经网络能够通过医学成像实现快速诊断。智能系统可以支持风险评估、决策制定和社会感知,从而改善疫情防控和公共卫生政策。此外,高通量虚拟筛选使人工智能能够加速治疗药物候选物的识别以及药物再利用的机会。最后,我们讨论了人工智能技术在抗击新冠疫情方面的未来研究方向,强调了跨学科合作的重要性。尽管前景广阔,但必须解决与模型泛化、数据质量、基础设施准备情况和伦理风险相关的障碍,以便将这些创新充分转化为实际影响。跨学科合作需要不同的专业知识和利益相关者参与,这对于开发强大、负责且以人为本的人工智能解决方案以应对新冠疫情和未来的突发公共卫生事件至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/10998276/6c2165d57085/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/10998276/5908be4deed4/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/10998276/174763c1a5d7/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/10998276/5e7e803ebd77/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/10998276/0d65c7054da6/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/10998276/4046b30f3e8d/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/10998276/6c2165d57085/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/10998276/5908be4deed4/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/10998276/174763c1a5d7/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/10998276/5e7e803ebd77/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/10998276/0d65c7054da6/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/10998276/4046b30f3e8d/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/10998276/6c2165d57085/gr5.jpg

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本文引用的文献

[1]
Modern technologies and solutions to enhance surveillance and response systems for emerging zoonotic diseases.

Sci One Health. 2023-12-12

[2]
Innovative applications of artificial intelligence in zoonotic disease management.

Sci One Health. 2023-11-3

[3]
An Epidemiological Neural Network Exploiting Dynamic Graph Structured Data Applied to the COVID-19 Outbreak.

IEEE Trans Big Data. 2020-10-21

[4]
Learning from prepandemic data to forecast viral escape.

Nature. 2023-10

[5]
Ethical considerations for the use of artificial intelligence in medical decision-making capacity assessments.

Psychiatry Res. 2023-10

[6]
Harnessing Deep Learning for Omics in an Era of COVID-19.

OMICS. 2023-4

[7]
Artificial Intelligence-Based Robust Hybrid Algorithm Design and Implementation for Real-Time Detection of Plant Diseases in Agricultural Environments.

Biology (Basel). 2022-11-29

[8]
Estimated global public health and economic impact of COVID-19 vaccines in the pre-omicron era using real-world empirical data.

Expert Rev Vaccines. 2023

[9]
Early Detection and Control of the Next Epidemic Wave Using Health Communications: Development of an Artificial Intelligence-Based Tool and Its Validation on COVID-19 Data from the US.

Int J Environ Res Public Health. 2022-11-30

[10]
COVID-19 detection on chest X-ray images using Homomorphic Transformation and VGG inspired deep convolutional neural network.

Biocybern Biomed Eng. 2023

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