• Int J Environ Res Public Health · Mar 2020

    Modeling the Research Landscapes of Artificial Intelligence Applications in Diabetes (GAPRESEARCH).

    • Giang Thu Vu, Bach Xuan Tran, Roger S McIntyre, Hai Quang Pham, Hai Thanh Phan, Giang Hai Ha, Kenneth K Gwee, Carl A Latkin, Ho Roger C M RCM 0000-0001-9629-4493 Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapor, and Ho Cyrus S H CSH Department of Psychological Medicine, National University Hospital, Singapore 119074, Singapore..
    • Center of Excellence in Evidence-based Medicine, Nguyen Tat Thanh University, Ho Chi Minh City 700000, Vietnam.
    • Int J Environ Res Public Health. 2020 Mar 17; 17 (6).

    AbstractThe rising prevalence and global burden of diabetes fortify the need for more comprehensive and effective management to prevent, monitor, and treat diabetes and its complications. Applying artificial intelligence in complimenting the diagnosis, management, and prediction of the diabetes trajectory has been increasingly common over the years. This study aims to illustrate an inclusive landscape of application of artificial intelligence in diabetes through a bibliographic analysis and offers future direction for research. Bibliometrics analysis was combined with exploratory factor analysis and latent Dirichlet allocation to uncover emergent research domains and topics related to artificial intelligence and diabetes. Data were extracted from the Web of Science Core Collection database. The results showed a rising trend in the number of papers and citations concerning AI applications in diabetes, especially since 2010. The nucleus driving the research and development of AI in diabetes is centered around developed countries, mainly consisting of the United States, which contributed 44.1% of the publications. Our analyses uncovered the top five emerging research domains to be: (i) use of artificial intelligence in diagnosis of diabetes, (ii) risk assessment of diabetes and its complications, (iii) role of artificial intelligence in novel treatments and monitoring in diabetes, (iv) application of telehealth and wearable technology in the daily management of diabetes, and (v) robotic surgical outcomes with diabetes as a comorbid. Despite the benefits of artificial intelligence, challenges with system accuracy, validity, and confidentiality breach will need to be tackled before being widely applied for patients' benefits.

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