Big Data Insights and Comprehensions in Industrial Healthcare: An Overview

Big data are the data which need to be shaped for their volume, size, and shape in order to extract meaningful information for an explicit purpose. Data are ever playing a significant role in organization and industry for their daily activities to functional smoothly. The volume of healthcare data i...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Mobile information systems 2021-01, Vol.2021, p.1-11
Hauptverfasser: He, Weiwei, Nazir, Shah, Hussain, Zahid
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 11
container_issue
container_start_page 1
container_title Mobile information systems
container_volume 2021
creator He, Weiwei
Nazir, Shah
Hussain, Zahid
description Big data are the data which need to be shaped for their volume, size, and shape in order to extract meaningful information for an explicit purpose. Data are ever playing a significant role in organization and industry for their daily activities to functional smoothly. The volume of healthcare data is increasing with the rising of technology and passage of time. This rise in volume of data can be a challenging task toward analysing the big data for industry and Internet of things (IoT). Numerous approaches, techniques, and tools exist in the literature for supporting, to handle, and manage processing of data. A review of the literature is needed in order to collect existing evidence from the literature to show which method or tool works for which particular situation. Therefore, the current study presents a review of the existing techniques of big data insights and scientific programming in the industry of healthcare. The report presents the summary of the literature. The study collects evidences from the existing literature and organizes it through the process of literature review with some derivations. This review will benefit practitioners to identify the right techniques for their specific purpose of research.
doi_str_mv 10.1155/2021/6628739
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2487052772</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2487052772</sourcerecordid><originalsourceid>FETCH-LOGICAL-c337t-12d6a923ef35a4b82b10b88e64eeab7f9f8c69b395a108bb63c4b89e6c08aeb93</originalsourceid><addsrcrecordid>eNp90E1PwkAQBuCN0UREb_6ATTxqZT-6X94QVDAkXDTh1uy2U7oEWtwtEP-9JXD2NJOZJzPJi9A9Jc-UCjFghNGBlEwrbi5Qj2olEkPE4rLrhUoTQtXiGt3EuCJEEi5UD32--iUe29biaR39smojtnWBR81mG6CCbtbUEfu6Wxe72AZv13gCdt1WuQ3wgoc1nu8h7D0cbtFVadcR7s61j77f375Gk2Q2_5iOhrMk51y1CWWFtIZxKLmwqdPMUeK0BpkCWKdKU-pcGseNsJRo5yTPO2VA5kRbcIb30cPp7jY0PzuIbbZqdqHuXmYs1YoIphTr1NNJ5aGJMUCZbYPf2PCbUZId08qOaWXntDr-eOKVrwt78P_rP-oDaSE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2487052772</pqid></control><display><type>article</type><title>Big Data Insights and Comprehensions in Industrial Healthcare: An Overview</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Wiley-Blackwell Open Access Titles</source><source>Alma/SFX Local Collection</source><creator>He, Weiwei ; Nazir, Shah ; Hussain, Zahid</creator><contributor>Jan, Mian Ahmad ; Mian Ahmad Jan</contributor><creatorcontrib>He, Weiwei ; Nazir, Shah ; Hussain, Zahid ; Jan, Mian Ahmad ; Mian Ahmad Jan</creatorcontrib><description>Big data are the data which need to be shaped for their volume, size, and shape in order to extract meaningful information for an explicit purpose. Data are ever playing a significant role in organization and industry for their daily activities to functional smoothly. The volume of healthcare data is increasing with the rising of technology and passage of time. This rise in volume of data can be a challenging task toward analysing the big data for industry and Internet of things (IoT). Numerous approaches, techniques, and tools exist in the literature for supporting, to handle, and manage processing of data. A review of the literature is needed in order to collect existing evidence from the literature to show which method or tool works for which particular situation. Therefore, the current study presents a review of the existing techniques of big data insights and scientific programming in the industry of healthcare. The report presents the summary of the literature. The study collects evidences from the existing literature and organizes it through the process of literature review with some derivations. This review will benefit practitioners to identify the right techniques for their specific purpose of research.</description><identifier>ISSN: 1574-017X</identifier><identifier>EISSN: 1875-905X</identifier><identifier>DOI: 10.1155/2021/6628739</identifier><language>eng</language><publisher>Amsterdam: Hindawi</publisher><subject>Big Data ; Cardiology ; Case studies ; Data analysis ; Electronic health records ; Health care ; Hospitals ; Internet of Things ; Laboratories ; Literature reviews ; Machine learning ; Physicians ; Public health ; Social networks</subject><ispartof>Mobile information systems, 2021-01, Vol.2021, p.1-11</ispartof><rights>Copyright © 2021 Weiwei He et al.</rights><rights>Copyright © 2021 Weiwei He et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c337t-12d6a923ef35a4b82b10b88e64eeab7f9f8c69b395a108bb63c4b89e6c08aeb93</citedby><cites>FETCH-LOGICAL-c337t-12d6a923ef35a4b82b10b88e64eeab7f9f8c69b395a108bb63c4b89e6c08aeb93</cites><orcidid>0000-0002-4416-5080 ; 0000-0003-0126-9944</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids></links><search><contributor>Jan, Mian Ahmad</contributor><contributor>Mian Ahmad Jan</contributor><creatorcontrib>He, Weiwei</creatorcontrib><creatorcontrib>Nazir, Shah</creatorcontrib><creatorcontrib>Hussain, Zahid</creatorcontrib><title>Big Data Insights and Comprehensions in Industrial Healthcare: An Overview</title><title>Mobile information systems</title><description>Big data are the data which need to be shaped for their volume, size, and shape in order to extract meaningful information for an explicit purpose. Data are ever playing a significant role in organization and industry for their daily activities to functional smoothly. The volume of healthcare data is increasing with the rising of technology and passage of time. This rise in volume of data can be a challenging task toward analysing the big data for industry and Internet of things (IoT). Numerous approaches, techniques, and tools exist in the literature for supporting, to handle, and manage processing of data. A review of the literature is needed in order to collect existing evidence from the literature to show which method or tool works for which particular situation. Therefore, the current study presents a review of the existing techniques of big data insights and scientific programming in the industry of healthcare. The report presents the summary of the literature. The study collects evidences from the existing literature and organizes it through the process of literature review with some derivations. This review will benefit practitioners to identify the right techniques for their specific purpose of research.</description><subject>Big Data</subject><subject>Cardiology</subject><subject>Case studies</subject><subject>Data analysis</subject><subject>Electronic health records</subject><subject>Health care</subject><subject>Hospitals</subject><subject>Internet of Things</subject><subject>Laboratories</subject><subject>Literature reviews</subject><subject>Machine learning</subject><subject>Physicians</subject><subject>Public health</subject><subject>Social networks</subject><issn>1574-017X</issn><issn>1875-905X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><recordid>eNp90E1PwkAQBuCN0UREb_6ATTxqZT-6X94QVDAkXDTh1uy2U7oEWtwtEP-9JXD2NJOZJzPJi9A9Jc-UCjFghNGBlEwrbi5Qj2olEkPE4rLrhUoTQtXiGt3EuCJEEi5UD32--iUe29biaR39smojtnWBR81mG6CCbtbUEfu6Wxe72AZv13gCdt1WuQ3wgoc1nu8h7D0cbtFVadcR7s61j77f375Gk2Q2_5iOhrMk51y1CWWFtIZxKLmwqdPMUeK0BpkCWKdKU-pcGseNsJRo5yTPO2VA5kRbcIb30cPp7jY0PzuIbbZqdqHuXmYs1YoIphTr1NNJ5aGJMUCZbYPf2PCbUZId08qOaWXntDr-eOKVrwt78P_rP-oDaSE</recordid><startdate>20210131</startdate><enddate>20210131</enddate><creator>He, Weiwei</creator><creator>Nazir, Shah</creator><creator>Hussain, Zahid</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-4416-5080</orcidid><orcidid>https://orcid.org/0000-0003-0126-9944</orcidid></search><sort><creationdate>20210131</creationdate><title>Big Data Insights and Comprehensions in Industrial Healthcare: An Overview</title><author>He, Weiwei ; Nazir, Shah ; Hussain, Zahid</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c337t-12d6a923ef35a4b82b10b88e64eeab7f9f8c69b395a108bb63c4b89e6c08aeb93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Big Data</topic><topic>Cardiology</topic><topic>Case studies</topic><topic>Data analysis</topic><topic>Electronic health records</topic><topic>Health care</topic><topic>Hospitals</topic><topic>Internet of Things</topic><topic>Laboratories</topic><topic>Literature reviews</topic><topic>Machine learning</topic><topic>Physicians</topic><topic>Public health</topic><topic>Social networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>He, Weiwei</creatorcontrib><creatorcontrib>Nazir, Shah</creatorcontrib><creatorcontrib>Hussain, Zahid</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Mobile information systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>He, Weiwei</au><au>Nazir, Shah</au><au>Hussain, Zahid</au><au>Jan, Mian Ahmad</au><au>Mian Ahmad Jan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Big Data Insights and Comprehensions in Industrial Healthcare: An Overview</atitle><jtitle>Mobile information systems</jtitle><date>2021-01-31</date><risdate>2021</risdate><volume>2021</volume><spage>1</spage><epage>11</epage><pages>1-11</pages><issn>1574-017X</issn><eissn>1875-905X</eissn><abstract>Big data are the data which need to be shaped for their volume, size, and shape in order to extract meaningful information for an explicit purpose. Data are ever playing a significant role in organization and industry for their daily activities to functional smoothly. The volume of healthcare data is increasing with the rising of technology and passage of time. This rise in volume of data can be a challenging task toward analysing the big data for industry and Internet of things (IoT). Numerous approaches, techniques, and tools exist in the literature for supporting, to handle, and manage processing of data. A review of the literature is needed in order to collect existing evidence from the literature to show which method or tool works for which particular situation. Therefore, the current study presents a review of the existing techniques of big data insights and scientific programming in the industry of healthcare. The report presents the summary of the literature. The study collects evidences from the existing literature and organizes it through the process of literature review with some derivations. This review will benefit practitioners to identify the right techniques for their specific purpose of research.</abstract><cop>Amsterdam</cop><pub>Hindawi</pub><doi>10.1155/2021/6628739</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-4416-5080</orcidid><orcidid>https://orcid.org/0000-0003-0126-9944</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1574-017X
ispartof Mobile information systems, 2021-01, Vol.2021, p.1-11
issn 1574-017X
1875-905X
language eng
recordid cdi_proquest_journals_2487052772
source Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Wiley-Blackwell Open Access Titles; Alma/SFX Local Collection
subjects Big Data
Cardiology
Case studies
Data analysis
Electronic health records
Health care
Hospitals
Internet of Things
Laboratories
Literature reviews
Machine learning
Physicians
Public health
Social networks
title Big Data Insights and Comprehensions in Industrial Healthcare: An Overview
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-18T20%3A29%3A44IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Big%20Data%20Insights%20and%20Comprehensions%20in%20Industrial%20Healthcare:%20An%20Overview&rft.jtitle=Mobile%20information%20systems&rft.au=He,%20Weiwei&rft.date=2021-01-31&rft.volume=2021&rft.spage=1&rft.epage=11&rft.pages=1-11&rft.issn=1574-017X&rft.eissn=1875-905X&rft_id=info:doi/10.1155/2021/6628739&rft_dat=%3Cproquest_cross%3E2487052772%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2487052772&rft_id=info:pmid/&rfr_iscdi=true