Global trends of big data analytics in health research: a bibliometric study
BackgroundThe field of “Big Health,” which encompasses the integration of big data in healthcare, has seen rapid development in recent years. As big data technologies continue to transform healthcare, understanding emerging trends and key advancements within the field is essential.MethodsWe retrieve...
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| Format: | Article |
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Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2025.1456286/full |
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| author | Li Yao Li Yao Yan Liu Tingrui Wang Chunyan Han Qiaoxing Li Qinqin Li Xiaoli You Tingting Ren Yinhua Wang |
| author_facet | Li Yao Li Yao Yan Liu Tingrui Wang Chunyan Han Qiaoxing Li Qinqin Li Xiaoli You Tingting Ren Yinhua Wang |
| author_sort | Li Yao |
| collection | DOAJ |
| description | BackgroundThe field of “Big Health,” which encompasses the integration of big data in healthcare, has seen rapid development in recent years. As big data technologies continue to transform healthcare, understanding emerging trends and key advancements within the field is essential.MethodsWe retrieved and filtered articles and reviews related to big data analytics in health research from the Web of Science Core Collection, including SCI Expanded and SSCI, covering the period from 2009 to 2024. Bibliometric and co-citation analyses were conducted using VOSviewer and CiteSpace.ResultsA total of 13,609 papers were analyzed, including 10,702 original research and 2,907 reviews. Co-occurrence word analysis identified six key research areas: (1) the application of big data analytics in health decision-making; (2) challenges in the technological management of health and medical big data; (3) integration of machine learning with health monitoring; (4) privacy and ethical issues in health and medical big data; (5) data integration in precision medicine; and (6) the use of big data in disease management and risk assessment. The co-word burst analysis results indicate that topics such as personalized medicine, decision support, and data protection experienced significant growth between 2015 and 2020. With the advancement of big data technologies, research hotspots have gradually expanded from basic data analysis to more complex application areas, such as the digital transformation of healthcare, digital health strategies, and smart health cities.ConclusionThis study highlights the growing impact of big data analytics in healthcare, emphasizing its role in decision-making, disease management, and precision medicine. As digital transformation in healthcare advances, addressing challenges in data integration, privacy, and machine learning integration will be crucial for maximizing the potential of big data technologies in improving health outcomes. |
| format | Article |
| id | doaj-art-dffa9037afa64df18bd326f56f2d835a |
| institution | Kabale University |
| issn | 2296-858X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Medicine |
| spelling | doaj-art-dffa9037afa64df18bd326f56f2d835a2025-08-20T03:29:52ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2025-07-011210.3389/fmed.2025.14562861456286Global trends of big data analytics in health research: a bibliometric studyLi Yao0Li Yao1Yan Liu2Tingrui Wang3Chunyan Han4Qiaoxing Li5Qinqin Li6Xiaoli You7Tingting Ren8Yinhua Wang9Department of Respiratory and Critical Care Medicine, The Affiliated Hospital of Guizhou Medical University, Guiyang, ChinaSchool of Management & Collaborative Innovation Laboratory of Digital Transformation and Governance, Guizhou University, Guiyang, ChinaSchool of Nursing, Guizhou Medical University, Guiyang, ChinaSchool of Nursing, Guizhou Medical University, Guiyang, ChinaEmergency Critical Care Unit, Qingdao Municipal Hospital Group, Qingdao, ChinaSchool of Management & Collaborative Innovation Laboratory of Digital Transformation and Governance, Guizhou University, Guiyang, ChinaSchool of Nursing, Guizhou Medical University, Guiyang, ChinaDepartment of Respiratory and Critical Care Medicine, The Affiliated Hospital of Guizhou Medical University, Guiyang, ChinaDepartment of Hepatobiliary Surgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, ChinaDepartment of Nursing, The Affiliated Hospital of Guizhou Medical University, Guiyang, ChinaBackgroundThe field of “Big Health,” which encompasses the integration of big data in healthcare, has seen rapid development in recent years. As big data technologies continue to transform healthcare, understanding emerging trends and key advancements within the field is essential.MethodsWe retrieved and filtered articles and reviews related to big data analytics in health research from the Web of Science Core Collection, including SCI Expanded and SSCI, covering the period from 2009 to 2024. Bibliometric and co-citation analyses were conducted using VOSviewer and CiteSpace.ResultsA total of 13,609 papers were analyzed, including 10,702 original research and 2,907 reviews. Co-occurrence word analysis identified six key research areas: (1) the application of big data analytics in health decision-making; (2) challenges in the technological management of health and medical big data; (3) integration of machine learning with health monitoring; (4) privacy and ethical issues in health and medical big data; (5) data integration in precision medicine; and (6) the use of big data in disease management and risk assessment. The co-word burst analysis results indicate that topics such as personalized medicine, decision support, and data protection experienced significant growth between 2015 and 2020. With the advancement of big data technologies, research hotspots have gradually expanded from basic data analysis to more complex application areas, such as the digital transformation of healthcare, digital health strategies, and smart health cities.ConclusionThis study highlights the growing impact of big data analytics in healthcare, emphasizing its role in decision-making, disease management, and precision medicine. As digital transformation in healthcare advances, addressing challenges in data integration, privacy, and machine learning integration will be crucial for maximizing the potential of big data technologies in improving health outcomes.https://www.frontiersin.org/articles/10.3389/fmed.2025.1456286/fullbig datahealthbibliometric studyVOSviewerCiteSpace |
| spellingShingle | Li Yao Li Yao Yan Liu Tingrui Wang Chunyan Han Qiaoxing Li Qinqin Li Xiaoli You Tingting Ren Yinhua Wang Global trends of big data analytics in health research: a bibliometric study Frontiers in Medicine big data health bibliometric study VOSviewer CiteSpace |
| title | Global trends of big data analytics in health research: a bibliometric study |
| title_full | Global trends of big data analytics in health research: a bibliometric study |
| title_fullStr | Global trends of big data analytics in health research: a bibliometric study |
| title_full_unstemmed | Global trends of big data analytics in health research: a bibliometric study |
| title_short | Global trends of big data analytics in health research: a bibliometric study |
| title_sort | global trends of big data analytics in health research a bibliometric study |
| topic | big data health bibliometric study VOSviewer CiteSpace |
| url | https://www.frontiersin.org/articles/10.3389/fmed.2025.1456286/full |
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