文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期，新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

利用人工智能技术抗击新冠疫情：综述

Using artificial intelligence technology to fight COVID-19: a review.

作者信息

Peng Yong, Liu Enbin, Peng Shanbi, Chen Qikun, Li Dangjian, Lian Dianpeng

机构信息

Petroleum Engineering School, Southwest Petroleum University, Chengdu, 610500 China.

School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, 610500 China.

出版信息

Artif Intell Rev. 2022;55(6):4941-4977. doi: 10.1007/s10462-021-10106-z. Epub 2022 Jan 3.

DOI:10.1007/s10462-021-10106-z
PMID:35002010
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8720541/
Abstract

In late December 2019, a new type of coronavirus was discovered, which was later named severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). Since its discovery, the virus has spread globally, with 2,975,875 deaths as of 15 April 2021, and has had a huge impact on our health systems and economy. How to suppress the continued spread of new coronary pneumonia is the main task of many scientists and researchers. The introduction of artificial intelligence technology has provided a huge contribution to the suppression of the new coronavirus. This article discusses the main application of artificial intelligence technology in the suppression of coronavirus from three major aspects of identification, prediction, and development through a large amount of literature research, and puts forward the current main challenges and possible development directions. The results show that it is an effective measure to combine artificial intelligence technology with a variety of new technologies to predict and identify COVID-19 patients.

摘要

2019年12月下旬，发现了一种新型冠状病毒，该病毒后来被命名为严重急性呼吸综合征冠状病毒2（SARS-CoV-2）。自发现以来，该病毒已在全球传播，截至2021年4月15日已造成2975875人死亡，并对我们的卫生系统和经济产生了巨大影响。如何抑制新冠肺炎的持续传播是许多科学家和研究人员的主要任务。人工智能技术的引入为抑制新型冠状病毒做出了巨大贡献。本文通过大量文献研究，从识别、预测和研发三个主要方面探讨了人工智能技术在抑制冠状病毒方面的主要应用，并提出了当前面临的主要挑战和可能的发展方向。结果表明，将人工智能技术与多种新技术相结合来预测和识别新冠肺炎患者是一种有效的措施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/2876331e6fa9/10462_2021_10106_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/9d647c7f03e4/10462_2021_10106_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/6f8a7d28eac1/10462_2021_10106_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/5f03096d5ce7/10462_2021_10106_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/ffbd3701e843/10462_2021_10106_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/9e1bc24cf66f/10462_2021_10106_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/e30def4418f8/10462_2021_10106_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/3d2126535399/10462_2021_10106_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/00bc1647f453/10462_2021_10106_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/1f2ee3b61e19/10462_2021_10106_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/3b6bf2a36169/10462_2021_10106_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/2037e87323a3/10462_2021_10106_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/deb867a94f81/10462_2021_10106_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/90a0875c28cc/10462_2021_10106_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/bce367dd0611/10462_2021_10106_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/2876331e6fa9/10462_2021_10106_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/9d647c7f03e4/10462_2021_10106_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/6f8a7d28eac1/10462_2021_10106_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/5f03096d5ce7/10462_2021_10106_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/ffbd3701e843/10462_2021_10106_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/9e1bc24cf66f/10462_2021_10106_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/e30def4418f8/10462_2021_10106_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/3d2126535399/10462_2021_10106_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/00bc1647f453/10462_2021_10106_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/1f2ee3b61e19/10462_2021_10106_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/3b6bf2a36169/10462_2021_10106_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/2037e87323a3/10462_2021_10106_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/deb867a94f81/10462_2021_10106_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/90a0875c28cc/10462_2021_10106_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/bce367dd0611/10462_2021_10106_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcfa/8720541/2876331e6fa9/10462_2021_10106_Fig15_HTML.jpg

相似文献

[1]
Using artificial intelligence technology to fight COVID-19: a review.

Artif Intell Rev. 2022

[2]
Approaches Based on Artificial Intelligence and the Internet of Intelligent Things to Prevent the Spread of COVID-19: Scoping Review.

J Med Internet Res. 2020-8-10

[3]
Artificial Intelligence (AI) applications for COVID-19 pandemic.

Diabetes Metab Syndr. 2020

[4]
[Applications of separation technology in novel coronavirus research, epidemic prevention and detection].

Se Pu. 2021-7-8

[5]
Application of Big Data and Artificial Intelligence in COVID-19 Prevention, Diagnosis, Treatment and Management Decisions in China.

J Med Syst. 2021-7-24

[6]
Integrating Digital Technologies and Public Health to Fight Covid-19 Pandemic: Key Technologies, Applications, Challenges and Outlook of Digital Healthcare.

Int J Environ Res Public Health. 2021-6-4

[7]
Current Strategies of Antiviral Drug Discovery for COVID-19.

Front Mol Biosci. 2021-5-13

[8]
Blockchain technologies to mitigate COVID-19 challenges: A scoping review.

Comput Methods Programs Biomed Update. 2021

[9]
Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-Like Epidemics: A Survey.

IEEE Access. 2021-6-30

[10]
Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review.

Chaos Solitons Fractals. 2020-10

引用本文的文献

[1]
Finding Consensus on Trust in AI in Health Care: Recommendations From a Panel of International Experts.

J Med Internet Res. 2025-2-19

[2]
Research on Artificial-Intelligence-Assisted Medicine: A Survey on Medical Artificial Intelligence.

Diagnostics (Basel). 2024-7-9

[3]
Identification of Dual Inhibitors Targeting Main Protease (M) and Cathepsin L as Potential Anti-SARS-CoV-2 Agents.

ACS Med Chem Lett. 2024-3-1

[4]
Academic publisher guidelines on AI usage: A ChatGPT supported thematic analysis.

F1000Res. 2023

[5]
Diagnostic Test Accuracy of Deep Learning Prediction Models on COVID-19 Severity: Systematic Review and Meta-Analysis.

J Med Internet Res. 2023-7-21

[6]
A Comprehensive Survey on Pandemic Patient Monitoring System: Enabling Technologies, Opportunities, and Research Challenges.

Wirel Pers Commun. 2023-6-2

[7]
Computer-aided methods for combating Covid-19 in prevention, detection, and service provision approaches.

Neural Comput Appl. 2023

[8]
Role of Drone Technology Helping in Alleviating the COVID-19 Pandemic.

Micromachines (Basel). 2022-9-25

[9]
Machine Learning and Deep Learning in Cardiothoracic Imaging: A Scoping Review.

Diagnostics (Basel). 2022-10-17

[10]
Comprehensive Survey of Machine Learning Systems for COVID-19 Detection.

J Imaging. 2022-9-30

本文引用的文献

[1]
Predicting the growth and trend of COVID-19 pandemic using machine learning and cloud computing.

Internet Things (Amst). 2020-9

[2]
A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research-An International Collaboration.

Epidemiologia (Basel). 2021-8-5

[3]
Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts.

IEEE Access. 2020-7-15

[4]
Anonymity Preserving IoT-Based COVID-19 and Other Infectious Disease Contact Tracing Model.

IEEE Access. 2020-8-31

[5]
A Blockchain and Artificial Intelligence-Based, Patient-Centric Healthcare System for Combating the COVID-19 Pandemic: Opportunities and Applications.

Healthcare (Basel). 2021-8-8

[6]
Masks use and facial dermatitis during COVID-19 outbreak: is there a difference between CE and non-CE approved masks? Multi-center, real-life data from a large Italian cohort.

Ital J Dermatol Venerol. 2021-4

[7]
An integrative drug repositioning framework discovered a potential therapeutic agent targeting COVID-19.

Signal Transduct Target Ther. 2021-4-24

[8]
A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19).

Eur Radiol. 2021-8

[9]
COVID-19 related masks increase severity of both acne (maskne) and rosacea (mask rosacea): Multi-center, real-life, telemedical, and observational prospective study.

Dermatol Ther. 2021-3

[10]
Mask-induced Koebner phenomenon and its clinical phenotypes: A multicenter, real-life study focusing on 873 dermatological consultations during COVID-19 pandemics.

Dermatol Ther. 2021-3

文献AI研究员

20分钟写一篇综述，助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索