Knowledge mapping of digital medicine in cardiovascular diseases from 2004 to 2022: A bibliometric analysis
Objective: To review studies on digital medicine in cardiovascular diseases (CVD), discuss its development process, knowledge structure and research hotspots, and provide a perspective for researchers in this field. Methods: The relevant literature in recent 20 years (January 2004 to October 2022) w...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-02-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024013495 |
| _version_ | 1797304500184154112 |
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| author | Ying Chen Xiang Xiao Qing He Rui-Qi Yao Gao-Yu Zhang Jia-Rong Fan Chong-Xiang Xue Li Huang |
| author_facet | Ying Chen Xiang Xiao Qing He Rui-Qi Yao Gao-Yu Zhang Jia-Rong Fan Chong-Xiang Xue Li Huang |
| author_sort | Ying Chen |
| collection | DOAJ |
| description | Objective: To review studies on digital medicine in cardiovascular diseases (CVD), discuss its development process, knowledge structure and research hotspots, and provide a perspective for researchers in this field. Methods: The relevant literature in recent 20 years (January 2004 to October 2022) were retrieved from the Web of Science Core Collection (WoSCC). CiteSpace was used to demonstrate our knowledge of keywords, co-references and speculative frontiers. VOSviewer was used to chart the contributions of authors, institutions and countries and incorporates their link strength into the table. Results: A total of 5265 English articles in set timespan were included. The number of publications increased steadily annually. The United States (US) produced the highest number of publications, followed by England. Most publications were from Harvard Medicine School, followed by Massachusetts General Hospital and Brigham Women's Hospital. The most authoritative academic journal was JMIR mHealth and uHealth. Noseworthy PA may have the highest influence in this intersected field with the highest number of citations and total link strength. The utilization of wearable mobile devices in the context of CVD, encompassing the identification of risk factors, diagnosis and prevention of diseases, as well as early intervention and remote management of diseases, has been widely acknowledged as a knowledge base and an area of current interest. To investigate the impact of various digital medicine interventions on chronic care and assess their clinical effectiveness, examine the potential of machine learning (ML) in delivering clinical care for atrial fibrillation (AF) and identifying early disease risk factors, as well as explore the development of disease prediction models using neural networks (NNs), ML and unsupervised learning in CVD prognosis, may emerge as future trends and areas of focus. Conclusion: Recently, there has been a significant surge of interest in the investigation of digital medicine in CVD. This initial bibliometric study offers a comprehensive analysis of the research landscape pertaining to digital medicine in CVD, thereby furnishing related scholars with a dependable reference to facilitate further progress in this domain. |
| first_indexed | 2024-03-08T00:10:24Z |
| format | Article |
| id | doaj.art-b23fbf84eb3643b58e1b4cedd5f29763 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-08T00:10:24Z |
| publishDate | 2024-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-b23fbf84eb3643b58e1b4cedd5f297632024-02-17T06:40:34ZengElsevierHeliyon2405-84402024-02-01103e25318Knowledge mapping of digital medicine in cardiovascular diseases from 2004 to 2022: A bibliometric analysisYing Chen0Xiang Xiao1Qing He2Rui-Qi Yao3Gao-Yu Zhang4Jia-Rong Fan5Chong-Xiang Xue6Li Huang7Beijing University of Chinese Medicine, Beijing, 100029, China; Department of Integrative Cardiology, China-Japan Friendship Hospital, Beijing, 100029, China; National Integrative Medicine Center for Cardiovascular Diseases, Beijing, 100029, China; National Center for Integrative Medicine, Beijing, 100029, ChinaDepartment of Integrative Cardiology, China-Japan Friendship Hospital, Beijing, 100029, China; National Integrative Medicine Center for Cardiovascular Diseases, Beijing, 100029, China; National Center for Integrative Medicine, Beijing, 100029, ChinaBeijing University of Chinese Medicine, Beijing, 100029, China; Department of Integrative Cardiology, China-Japan Friendship Hospital, Beijing, 100029, ChinaBeijing University of Chinese Medicine, Beijing, 100029, China; Department of Integrative Cardiology, China-Japan Friendship Hospital, Beijing, 100029, ChinaBeijing University of Chinese Medicine, Beijing, 100029, China; Department of Integrative Cardiology, China-Japan Friendship Hospital, Beijing, 100029, ChinaBeijing University of Chinese Medicine, Beijing, 100029, China; Department of Integrative Cardiology, China-Japan Friendship Hospital, Beijing, 100029, ChinaBeijing University of Chinese Medicine, Beijing, 100029, China; National Center for Integrative Medicine, Beijing, 100029, China; Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China; Corresponding author. Beijing University of Chinese Medicine, Beijing, 100029, China.Department of Integrative Cardiology, China-Japan Friendship Hospital, Beijing, 100029, China; National Integrative Medicine Center for Cardiovascular Diseases, Beijing, 100029, China; National Center for Integrative Medicine, Beijing, 100029, China; Corresponding author. Department of Integrative Cardiology, China-Japan Friendship Hospital, Beijing, 100029, China.Objective: To review studies on digital medicine in cardiovascular diseases (CVD), discuss its development process, knowledge structure and research hotspots, and provide a perspective for researchers in this field. Methods: The relevant literature in recent 20 years (January 2004 to October 2022) were retrieved from the Web of Science Core Collection (WoSCC). CiteSpace was used to demonstrate our knowledge of keywords, co-references and speculative frontiers. VOSviewer was used to chart the contributions of authors, institutions and countries and incorporates their link strength into the table. Results: A total of 5265 English articles in set timespan were included. The number of publications increased steadily annually. The United States (US) produced the highest number of publications, followed by England. Most publications were from Harvard Medicine School, followed by Massachusetts General Hospital and Brigham Women's Hospital. The most authoritative academic journal was JMIR mHealth and uHealth. Noseworthy PA may have the highest influence in this intersected field with the highest number of citations and total link strength. The utilization of wearable mobile devices in the context of CVD, encompassing the identification of risk factors, diagnosis and prevention of diseases, as well as early intervention and remote management of diseases, has been widely acknowledged as a knowledge base and an area of current interest. To investigate the impact of various digital medicine interventions on chronic care and assess their clinical effectiveness, examine the potential of machine learning (ML) in delivering clinical care for atrial fibrillation (AF) and identifying early disease risk factors, as well as explore the development of disease prediction models using neural networks (NNs), ML and unsupervised learning in CVD prognosis, may emerge as future trends and areas of focus. Conclusion: Recently, there has been a significant surge of interest in the investigation of digital medicine in CVD. This initial bibliometric study offers a comprehensive analysis of the research landscape pertaining to digital medicine in CVD, thereby furnishing related scholars with a dependable reference to facilitate further progress in this domain.http://www.sciencedirect.com/science/article/pii/S2405844024013495Digital medicineCardiovascular diseasesKnowledge-mapCiteSpaceVOSviewerReview |
| spellingShingle | Ying Chen Xiang Xiao Qing He Rui-Qi Yao Gao-Yu Zhang Jia-Rong Fan Chong-Xiang Xue Li Huang Knowledge mapping of digital medicine in cardiovascular diseases from 2004 to 2022: A bibliometric analysis Heliyon Digital medicine Cardiovascular diseases Knowledge-map CiteSpace VOSviewer Review |
| title | Knowledge mapping of digital medicine in cardiovascular diseases from 2004 to 2022: A bibliometric analysis |
| title_full | Knowledge mapping of digital medicine in cardiovascular diseases from 2004 to 2022: A bibliometric analysis |
| title_fullStr | Knowledge mapping of digital medicine in cardiovascular diseases from 2004 to 2022: A bibliometric analysis |
| title_full_unstemmed | Knowledge mapping of digital medicine in cardiovascular diseases from 2004 to 2022: A bibliometric analysis |
| title_short | Knowledge mapping of digital medicine in cardiovascular diseases from 2004 to 2022: A bibliometric analysis |
| title_sort | knowledge mapping of digital medicine in cardiovascular diseases from 2004 to 2022 a bibliometric analysis |
| topic | Digital medicine Cardiovascular diseases Knowledge-map CiteSpace VOSviewer Review |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024013495 |
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