Applications of artificial intelligence for hypertension management

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 adv...

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Bibliographic Details
Main 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
Format: Article
Language:English
Published: Wiley 2021-03-01
Series:The Journal of Clinical Hypertension
Online Access:https://doi.org/10.1111/jch.14180
Description
Summary: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.
ISSN:1524-6175
1751-7176