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Cited 2 time in webofscience Cited 2 time in scopus
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Applications of artificial intelligence for hypertension managementopen access

Authors
Tsoi, KelvinYiu, KarenLee, HelenCheng, Hao-MinWang, Tzung-DauTay, Jam-ChinTeo, Boon WeeTurana, YudaSoenarta, Arieska AnnSogunuru, Guru PrasadSiddique, SaulatChia, Yook-ChinShin, JinhoChen, Chen-HuanWang, Ji-GuangKario, Kazuomi
Issue Date
Mar-2021
Publisher
WILEY
Citation
JOURNAL OF CLINICAL HYPERTENSION, v.23, no.3, pp 568 - 574
Pages
7
Indexed
SCIE
SCOPUS
Journal Title
JOURNAL OF CLINICAL HYPERTENSION
Volume
23
Number
3
Start Page
568
End Page
574
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/7979
DOI
10.1111/jch.14180
ISSN
1524-6175
1751-7176
Abstract
The prevalence of hypertension is increasing along with an aging population, causing millions of premature deaths annually worldwide. Low awareness of blood pressure (BP) elevation and suboptimal hypertension diagnosis serve as the major hurdles in effective hypertension management. The advent of artificial intelligence (AI), however, sheds the light of new strategies for hypertension management, such as remote supports from telemedicine and big data-derived prediction. There is considerable evidence demonstrating the feasibility of AI applications in hypertension management. A foreseeable trend was observed in integrating BP measurements with various wearable sensors and smartphones, so as to permit continuous and convenient monitoring. In the meantime, further investigations are advised to validate the novel prediction and prognostic tools. These revolutionary developments have made a stride toward the future model for digital management of chronic diseases.
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서울 의과대학 > 서울 내과학교실 > 1. Journal Articles

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서울 의과대학 (DEPARTMENT OF INTERNAL MEDICINE)
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