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Applications of artificial intelligence for hypertension management

Authors :
Kelvin Tsoi
Karen Yiu
Helen Lee
Hao‐Min Cheng
Tzung‐Dau Wang
Jam‐Chin Tay
Boon Wee Teo
Yuda Turana
Arieska Ann Soenarta
Guru Prasad Sogunuru
Saulat Siddique
Yook‐Chin Chia
Jinho Shin
Chen‐Huan Chen
Ji‐Guang Wang
Kazuomi Kario
the HOPE Asia Network
Source :
The Journal of Clinical Hypertension, Vol 23, Iss 3, Pp 568-574 (2021)
Publication Year :
2021
Publisher :
Wiley, 2021.

Abstract

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.

Details

Language :
English
ISSN :
17517176 and 15246175
Volume :
23
Issue :
3
Database :
Directory of Open Access Journals
Journal :
The Journal of Clinical Hypertension
Publication Type :
Academic Journal
Accession number :
edsdoj.65df154bcdd548a193de7d53a56a1fbb
Document Type :
article
Full Text :
https://doi.org/10.1111/jch.14180