揭开医疗保健领域大数据分析的面纱:综合文献计量分析

Mohd Amran Mohd Daril, Fozia Fatima, Samar Raza Talpur, Alhamzah F. Abbas
{"title":"揭开医疗保健领域大数据分析的面纱:综合文献计量分析","authors":"Mohd Amran Mohd Daril, Fozia Fatima, Samar Raza Talpur, Alhamzah F. Abbas","doi":"10.3991/ijoe.v20i06.48085","DOIUrl":null,"url":null,"abstract":"In the rapidly evolving landscape of healthcare, the digital transformation marked by healthcare 4.0 has spurred a surge in data generation, giving rise to ‘big data’. Big data analytics has become an effective tool in the healthcare industry, revolutionising medical research, patient care, and healthcare management. This study undertakes a meticulous bibliometric analysis, drawing upon a dataset of 2212 articles from the Scopus database spanning 2014 to 2023, to unravel the trajectory of big data analytics in healthcare. The research explores diverse dimensions, from the distribution of studies across years to the productivity rankings of journals, countries, and institutions, elucidating the evolving trends and key contributors. Co-authorship networks and keyword co-occurrence analysis reveal thematic clusters and intellectual structures, contributing to a nuanced understanding of the field. The results underscore the escalating global interest in the fusion of big data and healthcare, illuminating collaborations, and identifying influential players. Additionally, the study identifies pressing challenges, including security concerns and skill shortages, emphasizing the imperative of overcoming these barriers for effective big data applications in healthcare. Serving as a valuable resource for researchers, practitioners, and policymakers, this research not only captures the current landscape but also provides insights for future exploration, contributing to strategic planning in this dynamic domain.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unveiling the Landscape of Big Data Analytics in Healthcare: A Comprehensive Bibliometric Analysis\",\"authors\":\"Mohd Amran Mohd Daril, Fozia Fatima, Samar Raza Talpur, Alhamzah F. Abbas\",\"doi\":\"10.3991/ijoe.v20i06.48085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the rapidly evolving landscape of healthcare, the digital transformation marked by healthcare 4.0 has spurred a surge in data generation, giving rise to ‘big data’. Big data analytics has become an effective tool in the healthcare industry, revolutionising medical research, patient care, and healthcare management. This study undertakes a meticulous bibliometric analysis, drawing upon a dataset of 2212 articles from the Scopus database spanning 2014 to 2023, to unravel the trajectory of big data analytics in healthcare. The research explores diverse dimensions, from the distribution of studies across years to the productivity rankings of journals, countries, and institutions, elucidating the evolving trends and key contributors. Co-authorship networks and keyword co-occurrence analysis reveal thematic clusters and intellectual structures, contributing to a nuanced understanding of the field. The results underscore the escalating global interest in the fusion of big data and healthcare, illuminating collaborations, and identifying influential players. Additionally, the study identifies pressing challenges, including security concerns and skill shortages, emphasizing the imperative of overcoming these barriers for effective big data applications in healthcare. Serving as a valuable resource for researchers, practitioners, and policymakers, this research not only captures the current landscape but also provides insights for future exploration, contributing to strategic planning in this dynamic domain.\",\"PeriodicalId\":507997,\"journal\":{\"name\":\"International Journal of Online and Biomedical Engineering (iJOE)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Online and Biomedical Engineering (iJOE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3991/ijoe.v20i06.48085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Online and Biomedical Engineering (iJOE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3991/ijoe.v20i06.48085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在快速发展的医疗保健领域,以医疗保健 4.0 为标志的数字化转型刺激了数据生成的激增,从而产生了 "大数据"。大数据分析已成为医疗保健行业的有效工具,彻底改变了医学研究、患者护理和医疗保健管理。本研究利用 Scopus 数据库中 2014 年至 2023 年的 2212 篇文章数据集,进行了细致的文献计量分析,以揭示大数据分析在医疗保健领域的发展轨迹。研究从不同年份的研究分布到期刊、国家和机构的生产力排名等多个维度进行了探讨,阐明了不断变化的趋势和主要贡献者。共同作者网络和关键词共现分析揭示了主题集群和知识结构,有助于深入了解该领域。研究结果强调了全球对大数据与医疗保健融合的兴趣不断升级,揭示了合作关系,并确定了有影响力的参与者。此外,研究还指出了紧迫的挑战,包括安全问题和技能短缺,强调了克服这些障碍以在医疗保健领域有效应用大数据的必要性。作为研究人员、从业人员和政策制定者的宝贵资源,本研究不仅把握了当前的形势,还为未来的探索提供了见解,有助于这一动态领域的战略规划。
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
Unveiling the Landscape of Big Data Analytics in Healthcare: A Comprehensive Bibliometric Analysis
In the rapidly evolving landscape of healthcare, the digital transformation marked by healthcare 4.0 has spurred a surge in data generation, giving rise to ‘big data’. Big data analytics has become an effective tool in the healthcare industry, revolutionising medical research, patient care, and healthcare management. This study undertakes a meticulous bibliometric analysis, drawing upon a dataset of 2212 articles from the Scopus database spanning 2014 to 2023, to unravel the trajectory of big data analytics in healthcare. The research explores diverse dimensions, from the distribution of studies across years to the productivity rankings of journals, countries, and institutions, elucidating the evolving trends and key contributors. Co-authorship networks and keyword co-occurrence analysis reveal thematic clusters and intellectual structures, contributing to a nuanced understanding of the field. The results underscore the escalating global interest in the fusion of big data and healthcare, illuminating collaborations, and identifying influential players. Additionally, the study identifies pressing challenges, including security concerns and skill shortages, emphasizing the imperative of overcoming these barriers for effective big data applications in healthcare. Serving as a valuable resource for researchers, practitioners, and policymakers, this research not only captures the current landscape but also provides insights for future exploration, contributing to strategic planning in this dynamic domain.
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
XAI-PhD: Fortifying Trust of Phishing URL Detection Empowered by Shapley Additive Explanations Improving the Accuracy of Oncology Diagnosis: A Machine Learning-Based Approach to Cancer Prediction Social Robots, Mindfulness, and Kindergarten Blockchain of Things for Securing and Managing Water 4.0 Applications Intelligent Interconnected Healthcare System: Integrating IoT and Big Data for Personalized Patient Care
×
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