人工智能和机器学习对 COVID-19 相关询问的答复。

Q3 Engineering Journal of Medical Engineering and Technology Pub Date : 2023-08-01 Epub Date: 2024-04-16 DOI:10.1080/03091902.2024.2321846
Naser Zaeri
{"title":"人工智能和机器学习对 COVID-19 相关询问的答复。","authors":"Naser Zaeri","doi":"10.1080/03091902.2024.2321846","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":39637,"journal":{"name":"Journal of Medical Engineering and Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence and machine learning responses to COVID-19 related inquiries.\",\"authors\":\"Naser Zaeri\",\"doi\":\"10.1080/03091902.2024.2321846\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":39637,\"journal\":{\"name\":\"Journal of Medical Engineering and Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Medical Engineering and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/03091902.2024.2321846\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/4/16 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/03091902.2024.2321846","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/4/16 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0

摘要

最近,人工智能和机器学习取得了突破性进展,研究人员和科学家可以利用基于计算的模型将关联数据转化为有用信息,从而帮助疾病诊断、检查和病毒遏制。在本文中,我们广泛研究了人工智能和机器学习在 COVID-19 大流行开始近四年后的高效应对中发挥的作用。在这方面,我们研究了多个学科的学术和研究团体开展的大量重要研究,以及人工智能算法的实际应用,这些算法为调查不同的 COVID-19 决策场景提出了潜在的解决方案。我们确定了人工智能和机器学习可对这一背景产生影响的众多领域,包括诊断(使用胸部 X 光成像和 CT 成像)、严重程度、跟踪、治疗和制药业。此外,我们还分析了这一困境的局限性、限制和危害。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Artificial intelligence and machine learning responses to COVID-19 related inquiries.

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Medical Engineering and Technology
Journal of Medical Engineering and Technology Engineering-Biomedical Engineering
CiteScore
4.60
自引率
0.00%
发文量
77
期刊介绍: The Journal of Medical Engineering & Technology is an international, independent, multidisciplinary, bimonthly journal promoting an understanding of the physiological processes underlying disease processes and the appropriate application of technology. Features include authoritative review papers, the reporting of original research, and evaluation reports on new and existing techniques and devices. Each issue of the journal contains a comprehensive information service which provides news relevant to the world of medical technology, details of new products, book reviews, and selected contents of related journals.
期刊最新文献
News and product update. Safety, feasibility, and acceptability of a novel device to monitor ischaemic stroke patients. An enhanced Garter Snake Optimization-assisted deep learning model for lung cancer segmentation and classification using CT images. Transformative applications of additive manufacturing in biomedical engineering: bioprinting to surgical innovations. Characterisation of pulmonary air leak measurements using a mechanical ventilator in a bench setup.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1