2019冠状病毒病筛查、测试和治疗中的智能医疗设备和应用程序、基于机器学习的自动诊断系统和实时医疗数据分析

Ann Kucera Jiri Stanley
{"title":"2019冠状病毒病筛查、测试和治疗中的智能医疗设备和应用程序、基于机器学习的自动诊断系统和实时医疗数据分析","authors":"Ann Kucera Jiri Stanley","doi":"10.22381/ajmr8220218","DOIUrl":null,"url":null,"abstract":"(Zhang and Han, 2020) Real-time patient monitoring and biomedical big data are determining in disease prediction, diagnosis, and support clinical decision by use of artificial intelligence-enabled wearable medical devices and machine learning-based automated diagnostic systems. Study Design, Survey Methods, and Materials The interviews were conducted online and data were weighted by five variables (age, race/ethnicity, gender, education, and geographic region) using the Census Bureau's American Community Survey to reflect reliably and accurately the demographic composition of the United States. (Chen et al., 2020) COVID-19 detection and monitoring systems can be put into action throughout an Internet of Medical Things infrastructure, monitoring both potential and confirmed patients in real time, and as regards the treatment responses of recovered individuals, while grasping the nature of the virus by acquiring, inspecting, and archiving valuable data. (Bordel et al., 2020) Internet of Medical Things deploys networked medical devices and wireless communication to facilitate the sharing of healthcare data through artificial intelligence-based diagnostic algorithms, real-time medical data analytics, and machine learning-based automated diagnostic systems.","PeriodicalId":91446,"journal":{"name":"American journal of medical research (New York, N.Y.)","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Smart Healthcare Devices and Applications, Machine Learning-based Automated Diagnostic Systems, and Real-Time Medical Data Analytics in COVID-19 Screening, Testing, and Treatment\",\"authors\":\"Ann Kucera Jiri Stanley\",\"doi\":\"10.22381/ajmr8220218\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"(Zhang and Han, 2020) Real-time patient monitoring and biomedical big data are determining in disease prediction, diagnosis, and support clinical decision by use of artificial intelligence-enabled wearable medical devices and machine learning-based automated diagnostic systems. Study Design, Survey Methods, and Materials The interviews were conducted online and data were weighted by five variables (age, race/ethnicity, gender, education, and geographic region) using the Census Bureau's American Community Survey to reflect reliably and accurately the demographic composition of the United States. (Chen et al., 2020) COVID-19 detection and monitoring systems can be put into action throughout an Internet of Medical Things infrastructure, monitoring both potential and confirmed patients in real time, and as regards the treatment responses of recovered individuals, while grasping the nature of the virus by acquiring, inspecting, and archiving valuable data. (Bordel et al., 2020) Internet of Medical Things deploys networked medical devices and wireless communication to facilitate the sharing of healthcare data through artificial intelligence-based diagnostic algorithms, real-time medical data analytics, and machine learning-based automated diagnostic systems.\",\"PeriodicalId\":91446,\"journal\":{\"name\":\"American journal of medical research (New York, N.Y.)\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American journal of medical research (New York, N.Y.)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22381/ajmr8220218\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of medical research (New York, N.Y.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22381/ajmr8220218","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

(Zhang and Han, 2020)通过使用支持人工智能的可穿戴医疗设备和基于机器学习的自动诊断系统,实时患者监测和生物医学大数据在疾病预测、诊断和支持临床决策方面发挥着重要作用。研究设计、调查方法和材料访谈是在线进行的,数据采用人口普查局美国社区调查的五个变量(年龄、种族/民族、性别、教育程度和地理区域)加权,以可靠和准确地反映美国的人口构成。(Chen et al., 2020) COVID-19检测和监测系统可以在整个医疗物联网基础设施中投入使用,实时监测潜在患者和确诊患者,以及康复个体的治疗反应,同时通过获取、检查和存档有价值的数据来掌握病毒的性质。(Bordel et al., 2020)医疗物联网部署联网医疗设备和无线通信,通过基于人工智能的诊断算法、实时医疗数据分析和基于机器学习的自动诊断系统,促进医疗数据的共享。
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
Smart Healthcare Devices and Applications, Machine Learning-based Automated Diagnostic Systems, and Real-Time Medical Data Analytics in COVID-19 Screening, Testing, and Treatment
(Zhang and Han, 2020) Real-time patient monitoring and biomedical big data are determining in disease prediction, diagnosis, and support clinical decision by use of artificial intelligence-enabled wearable medical devices and machine learning-based automated diagnostic systems. Study Design, Survey Methods, and Materials The interviews were conducted online and data were weighted by five variables (age, race/ethnicity, gender, education, and geographic region) using the Census Bureau's American Community Survey to reflect reliably and accurately the demographic composition of the United States. (Chen et al., 2020) COVID-19 detection and monitoring systems can be put into action throughout an Internet of Medical Things infrastructure, monitoring both potential and confirmed patients in real time, and as regards the treatment responses of recovered individuals, while grasping the nature of the virus by acquiring, inspecting, and archiving valuable data. (Bordel et al., 2020) Internet of Medical Things deploys networked medical devices and wireless communication to facilitate the sharing of healthcare data through artificial intelligence-based diagnostic algorithms, real-time medical data analytics, and machine learning-based automated diagnostic systems.
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
自引率
0.00%
发文量
0
期刊最新文献
Internet of Medical Things-based Clinical Decision Support Systems, Smart Healthcare Wearable Devices, and Machine Learning Algorithms in COVID-19 Prevention, Screening, Detection, Diagnosis, and Treatment Internet of Medical Things-driven Remote Monitoring Systems, Big Healthcare Data Analytics, and Wireless Body Area Networks in COVID-19 Detection and Diagnosis Resting Motor Threshold (RMT) during “Preservation” Transcranial Magnetic Stimulation (TMS) Machine and Deep Learning Algorithms, Computer Vision Technologies, and Internet of Things-based Healthcare Monitoring Systems in COVID-19 Prevention, Testing, Detection, and Treatment Smart Wearable Internet of Medical Things Technologies, Artificial Intelligence-based Diagnostic Algorithms, and Real-Time Healthcare Monitoring Systems in COVID-19 Detection and Treatment
×
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