{"title":"基于物联网的健康监测系统、人工智能驱动的诊断算法和身体区域传感器网络在COVID-19预防、筛查和治疗中的应用","authors":"Peter Bowles","doi":"10.22381/ajmr9120228","DOIUrl":null,"url":null,"abstract":"Despite the relevance of Internet of Things-based health monitoring systems, artificial intelligence-driven diagnostic algorithms, and body area sensor networks in COVID-19 prevention, screening, and treatment, only limited research has been conducted on this topic. Throughout January 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including \"COVID-19\" + \"Internet of Things-based health monitoring systems,\" \"artificial intelligence-driven diagnostic algorithms,\" and \"body area sensor networks.\" Keywords: Internet of Medical Things;COVID-19;body area sensor network 1.Introduction The purpose of my systematic review is to examine the recently published literature on COVID-19 prevention, screening, and treatment, and integrate the insights it configures on Internet of Things-based health monitoring systems, artificial intelligence-driven diagnostic algorithms, and body area sensor networks. Sensitive physiological data collected by medical sensor devices can be instrumental in COVID-19 prevention, clinical observation, visual data analysis, patient diagnosis, contact tracing, and intervention processes, optimizing Internet of Medical Things system interoperability. 3.Methodology Throughout January 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including \"COVID-19\" + \"Internet of Things-based health monitoring systems,\" \"artificial intelligence-driven diagnostic algorithms,\" and \"body area sensor networks.\" Sensitive physiological data collected by medical sensor devices can be instrumental in COVID-19 prevention, clinical observation, visual data analysis, patient diagnosis, contact tracing, and intervention processes, optimizing Internet of Medical Things system interoperability.","PeriodicalId":91446,"journal":{"name":"American journal of medical research (New York, N.Y.)","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Internet of Things-based Health Monitoring Systems, Artificial Intelligence-driven Diagnostic Algorithms, and Body Area Sensor Networks in COVID-19 Prevention, Screening, and Treatment\",\"authors\":\"Peter Bowles\",\"doi\":\"10.22381/ajmr9120228\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Despite the relevance of Internet of Things-based health monitoring systems, artificial intelligence-driven diagnostic algorithms, and body area sensor networks in COVID-19 prevention, screening, and treatment, only limited research has been conducted on this topic. Throughout January 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including \\\"COVID-19\\\" + \\\"Internet of Things-based health monitoring systems,\\\" \\\"artificial intelligence-driven diagnostic algorithms,\\\" and \\\"body area sensor networks.\\\" Keywords: Internet of Medical Things;COVID-19;body area sensor network 1.Introduction The purpose of my systematic review is to examine the recently published literature on COVID-19 prevention, screening, and treatment, and integrate the insights it configures on Internet of Things-based health monitoring systems, artificial intelligence-driven diagnostic algorithms, and body area sensor networks. Sensitive physiological data collected by medical sensor devices can be instrumental in COVID-19 prevention, clinical observation, visual data analysis, patient diagnosis, contact tracing, and intervention processes, optimizing Internet of Medical Things system interoperability. 3.Methodology Throughout January 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including \\\"COVID-19\\\" + \\\"Internet of Things-based health monitoring systems,\\\" \\\"artificial intelligence-driven diagnostic algorithms,\\\" and \\\"body area sensor networks.\\\" Sensitive physiological data collected by medical sensor devices can be instrumental in COVID-19 prevention, clinical observation, visual data analysis, patient diagnosis, contact tracing, and intervention processes, optimizing Internet of Medical Things system interoperability.\",\"PeriodicalId\":91446,\"journal\":{\"name\":\"American journal of medical research (New York, N.Y.)\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American journal of medical research (New York, N.Y.)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22381/ajmr9120228\",\"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/ajmr9120228","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
尽管基于物联网的健康监测系统、人工智能驱动的诊断算法和身体区域传感器网络在COVID-19的预防、筛查和治疗中具有相关性，但对此主题的研究却非常有限。在整个2022年1月，我对Web of Science、Scopus和ProQuest数据库进行了定量文献综述，搜索词包括“COVID-19”+“基于物联网的健康监测系统”、“人工智能驱动的诊断算法”和“身体区域传感器网络”。关键词:医疗物联网;COVID-19;体区传感器网络我的系统综述的目的是研究最近发表的关于COVID-19预防、筛查和治疗的文献，并整合其对基于物联网的健康监测系统、人工智能驱动的诊断算法和身体区域传感器网络的见解。医疗传感器设备采集的敏感生理数据可用于COVID-19预防、临床观察、可视化数据分析、患者诊断、接触者追踪和干预流程，优化医疗物联网系统互操作性。3.在整个2022年1月，我们对Web of Science、Scopus和ProQuest数据库进行了定量文献综述，搜索词包括“COVID-19”+“基于物联网的健康监测系统”、“人工智能驱动的诊断算法”和“身体区域传感器网络”。医疗传感器设备采集的敏感生理数据可用于COVID-19预防、临床观察、可视化数据分析、患者诊断、接触者追踪和干预流程，优化医疗物联网系统互操作性。
Internet of Things-based Health Monitoring Systems, Artificial Intelligence-driven Diagnostic Algorithms, and Body Area Sensor Networks in COVID-19 Prevention, Screening, and Treatment
Despite the relevance of Internet of Things-based health monitoring systems, artificial intelligence-driven diagnostic algorithms, and body area sensor networks in COVID-19 prevention, screening, and treatment, only limited research has been conducted on this topic. Throughout January 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including "COVID-19" + "Internet of Things-based health monitoring systems," "artificial intelligence-driven diagnostic algorithms," and "body area sensor networks." Keywords: Internet of Medical Things;COVID-19;body area sensor network 1.Introduction The purpose of my systematic review is to examine the recently published literature on COVID-19 prevention, screening, and treatment, and integrate the insights it configures on Internet of Things-based health monitoring systems, artificial intelligence-driven diagnostic algorithms, and body area sensor networks. Sensitive physiological data collected by medical sensor devices can be instrumental in COVID-19 prevention, clinical observation, visual data analysis, patient diagnosis, contact tracing, and intervention processes, optimizing Internet of Medical Things system interoperability. 3.Methodology Throughout January 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including "COVID-19" + "Internet of Things-based health monitoring systems," "artificial intelligence-driven diagnostic algorithms," and "body area sensor networks." Sensitive physiological data collected by medical sensor devices can be instrumental in COVID-19 prevention, clinical observation, visual data analysis, patient diagnosis, contact tracing, and intervention processes, optimizing Internet of Medical Things system interoperability.
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