A Study on COVID-19 Prediction and Detection With Artificial Intelligence-Based Real-Time Healthcare Monitoring Systems
Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old...
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description | Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.
Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students. |
doi_str_mv | 10.4018/978-1-7998-7188-0.ch004 |
format | Book Chapter |
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Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.</description><identifier>ISBN: 1799871886</identifier><identifier>ISBN: 9781799871880</identifier><identifier>EISBN: 9781799871903</identifier><identifier>EISBN: 1799871908</identifier><identifier>DOI: 10.4018/978-1-7998-7188-0.ch004</identifier><identifier>OCLC: 1264475562</identifier><identifier>LCCallNum: RA652.2.M3 M33</identifier><language>eng</language><publisher>United States: IGI Global</publisher><subject>Data processing. | Epidemics ; Epidemiology ; Machine Learning ; Mathematical models. | Machine learning. | Artificial intelligence ; Medical applications ; Medical Technologies ; Medicine & Healthcare</subject><ispartof>Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease, 2021, p.52-63</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://coverimages.igi-global.com/cover-images/covers/9781799871880.png</thumbnail><link.rule.ids>777,778,782,791,23125,27912</link.rule.ids></links><search><contributor>Roy, Manikant</contributor><contributor>Gupta, Lovi Raj</contributor><creatorcontrib>Roy, Manikant</creatorcontrib><creatorcontrib>Gupta, Lovi Raj</creatorcontrib><title>A Study on COVID-19 Prediction and Detection With Artificial Intelligence-Based Real-Time Healthcare Monitoring Systems</title><title>Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease</title><description>Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.
Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.</description><subject>Data processing. | Epidemics</subject><subject>Epidemiology</subject><subject>Machine Learning</subject><subject>Mathematical models. | Machine learning. | Artificial intelligence</subject><subject>Medical applications</subject><subject>Medical Technologies</subject><subject>Medicine & Healthcare</subject><isbn>1799871886</isbn><isbn>9781799871880</isbn><isbn>9781799871903</isbn><isbn>1799871908</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>2021</creationdate><recordtype>book_chapter</recordtype><recordid>eNplUdFOAjEQrDEaFfkG-wPFttdrr48IKiQYjBB9bMrdlqsed3gtMfy9h_Dm087MzmyyGYTuGB0IyrJ7rTLCiNI6I4plGaGDvKRUnKF-t2EHXTFNk3N0cyJZJi87wqUQKk0lv0L9ED4ppVwoxoW8Rj9DvIi7Yo-bGo_m79MxYRq_tlD4PPpOs3WBxxDhyD58LPGwjd753NsKT-sIVeXXUOdAHmyAAr-BrcjSbwBPOhTL3LaAX5rax6b19Rov9iHCJtyiC2erAP3T7KHl0-NyNCGz-fN0NJwRnwlNnFUps5YVwuWCS20F07IQALbDiYCV6z5LJHdSF1oljDvtpJIydVQnrLP0ED-e3bbN9w5CNLBqmq8c6tjaKi_tNkIbjJRacyoM40bqLkSPIb_25mAPhlFzaMD8a8D8NZD8AvYvdgc</recordid><startdate>20210625</startdate><enddate>20210625</enddate><creator>Roy, Manikant</creator><creator>Gupta, Lovi Raj</creator><general>IGI Global</general><scope>FFUUA</scope></search><sort><creationdate>20210625</creationdate><title>A Study on COVID-19 Prediction and Detection With Artificial Intelligence-Based Real-Time Healthcare Monitoring Systems</title><author>Roy, Manikant ; Gupta, Lovi Raj</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i849-fa751aa1d4fc4269a4196d4eea69a34ebf644362f69d97312f9f67665f09319a3</frbrgroupid><rsrctype>book_chapters</rsrctype><prefilter>book_chapters</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Data processing. | Epidemics</topic><topic>Epidemiology</topic><topic>Machine Learning</topic><topic>Mathematical models. | Machine learning. | Artificial intelligence</topic><topic>Medical applications</topic><topic>Medical Technologies</topic><topic>Medicine & Healthcare</topic><toplevel>online_resources</toplevel><creatorcontrib>Roy, Manikant</creatorcontrib><creatorcontrib>Gupta, Lovi Raj</creatorcontrib><collection>ProQuest Ebook Central - Book Chapters - Demo use only</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Roy, Manikant</au><au>Gupta, Lovi Raj</au><au>Roy, Manikant</au><au>Gupta, Lovi Raj</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>A Study on COVID-19 Prediction and Detection With Artificial Intelligence-Based Real-Time Healthcare Monitoring Systems</atitle><btitle>Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease</btitle><date>2021-06-25</date><risdate>2021</risdate><spage>52</spage><epage>63</epage><pages>52-63</pages><isbn>1799871886</isbn><isbn>9781799871880</isbn><eisbn>9781799871903</eisbn><eisbn>1799871908</eisbn><abstract>Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. 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Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.</abstract><cop>United States</cop><pub>IGI Global</pub><doi>10.4018/978-1-7998-7188-0.ch004</doi><oclcid>1264475562</oclcid><tpages>12</tpages></addata></record> |
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ispartof | Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease, 2021, p.52-63 |
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source | InfoSci-Books |
subjects | Data processing. | Epidemics Epidemiology Machine Learning Mathematical models. | Machine learning. | Artificial intelligence Medical applications Medical Technologies Medicine & Healthcare |
title | A Study on COVID-19 Prediction and Detection With Artificial Intelligence-Based Real-Time Healthcare Monitoring Systems |
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