Smart Wearable Internet of Medical Things Technologies, Artificial Intelligence-based Diagnostic Algorithms, and Real-Time Healthcare Monitoring Systems in COVID-19 Detection and Treatment
Barbara Cug Juraj Michalikova Katarina Frajtova Crowell
{"title":"Smart Wearable Internet of Medical Things Technologies, Artificial Intelligence-based Diagnostic Algorithms, and Real-Time Healthcare Monitoring Systems in COVID-19 Detection and Treatment","authors":"Barbara Cug Juraj Michalikova Katarina Frajtova Crowell","doi":"10.22381/ajmr9120222","DOIUrl":null,"url":null,"abstract":"Keywords: Internet of Medical Things;diagnostic algorithm;COVID-19 1.Introduction The purpose of our systematic review is to examine the recently published literature on COVID-19 detection and treatment and integrate the insights it configures on smart wearable Internet of Medical Things technologies, artificial intelligence-based diagnostic algorithms, and real-time healthcare monitoring systems. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), networked sensors, wearable devices, and smart clinical systems (section 4), real-time healthcare monitoring systems and processing algorithms in Internet of Medical Things (section 5), smart personalized healthcare applications and services (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). 4.Networked Sensors, Wearable Devices, and Smart Clinical Systems Internet of Medical Things is pivotal in heterogeneous clinical trials, disease monitoring, and healthcare procedures (Gul et al., 2021;Maitra et al., 2021;Scrugli et al., 2022) through wireless data collection, analysis, and sharing. Specialized machine learning and predictive algorithms can be pivotal in preventive screenings, monitoring vital signs and life-threatening conditions, and supporting clinical judgment in COVID-19 early recognition and treatment by analyzing patient records and clinical data.","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":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of medical research (New York, N.Y.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22381/ajmr9120222","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Keywords: Internet of Medical Things;diagnostic algorithm;COVID-19 1.Introduction The purpose of our systematic review is to examine the recently published literature on COVID-19 detection and treatment and integrate the insights it configures on smart wearable Internet of Medical Things technologies, artificial intelligence-based diagnostic algorithms, and real-time healthcare monitoring systems. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), networked sensors, wearable devices, and smart clinical systems (section 4), real-time healthcare monitoring systems and processing algorithms in Internet of Medical Things (section 5), smart personalized healthcare applications and services (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). 4.Networked Sensors, Wearable Devices, and Smart Clinical Systems Internet of Medical Things is pivotal in heterogeneous clinical trials, disease monitoring, and healthcare procedures (Gul et al., 2021;Maitra et al., 2021;Scrugli et al., 2022) through wireless data collection, analysis, and sharing. Specialized machine learning and predictive algorithms can be pivotal in preventive screenings, monitoring vital signs and life-threatening conditions, and supporting clinical judgment in COVID-19 early recognition and treatment by analyzing patient records and clinical data.