Please use this identifier to cite or link to this item:
Title: The current research landscape of the application of artificial intelligence in managing cerebrovascular and heart diseases: A bibliometric and content analysis
Authors: Tran, B.X.
Latkin, C.A.
Vu, G.T.
Nguyen, H.L.T.
Nghiem, S.
Tan, M.-X.
Lim, Z.-K.
Ho, C.S.H. 
Ho, R.C.M. 
Keywords: Artificial intelligence
Heart diseases
Issue Date: 2019
Publisher: MDPI AG
Citation: Tran, B.X., Latkin, C.A., Vu, G.T., Nguyen, H.L.T., Nghiem, S., Tan, M.-X., Lim, Z.-K., Ho, C.S.H., Ho, R.C.M. (2019). The current research landscape of the application of artificial intelligence in managing cerebrovascular and heart diseases: A bibliometric and content analysis. International Journal of Environmental Research and Public Health 16 (15) : 2699. ScholarBank@NUS Repository.
Rights: Attribution 4.0 International
Abstract: The applications of artificial intelligence (AI) in aiding clinical decision-making and management of stroke and heart diseases have become increasingly common in recent years, thanks in part to technological advancements and the heightened interest of the research and medical community. This study aims to provide a comprehensive picture of global trends and developments of AI applications relating to stroke and heart diseases, identifying research gaps and suggesting future directions for research and policy-making. A novel analysis approach that combined bibliometrics analysis with a more complex analysis of abstract content using exploratory factor analysis and Latent Dirichlet allocation, which uncovered emerging research domains and topics, was adopted. Data were extracted from the Web of Science database. Results showed topics with the most compelling growth to be AI for big data analysis, robotic prosthesis, robotics-assisted stroke rehabilitation, and minimally invasive surgery. The study also found an emerging landscape of research that was centered on population-specific and early detection of stroke and heart disease. Application of AI in health behavior tracking and improvement as well as the use of robotics in medical diagnostics and prognostication have also been found to attract significant research attention. In light of these findings, it is suggested that the currently under-researched issues of data management, AI model reliability, as well as validation of its clinical utility, need to be further explored in future research and policy decisions to maximize the benefits of AI applications in stroke and heart diseases. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.
Source Title: International Journal of Environmental Research and Public Health
ISSN: 16617827
DOI: 10.3390/ijerph16152699
Rights: Attribution 4.0 International
Appears in Collections:Elements
Staff Publications

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
10_3390_ijerph16152699.pdf2.53 MBAdobe PDF



Google ScholarTM



This item is licensed under a Creative Commons License Creative Commons