Applications of artificial intelligence for hypertension management
Journal
Journal of clinical hypertension (Greenwich, Conn.)
Journal Volume
23
Journal Issue
3
Pages
568
Date Issued
2021-03
Author(s)
Tsoi, Kelvin
Yiu, Karen
Lee, Helen
Cheng, Hao-Min
Tay, Jam-Chin
Teo, Boon Wee
Turana, Yuda
Soenarta, Arieska Ann
Sogunuru, Guru Prasad
Siddique, Saulat
Chia, Yook-Chin
Shin, Jinho
Chen, Chen-Huan
Wang, Ji-Guang
Kario, Kazuomi
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.
SDGs
Other Subjects
antihypertensive agent; antihypertensive therapy; artificial intelligence; blood pressure monitoring; blood pressure regulation; disease burden; feasibility study; health care cost; human; hypertension; incidence; lifestyle modification; mobile application; outcome assessment; prediction; prognosis; Review; telemedicine; trend study; validation process; aged; artificial intelligence; hypertension; telemedicine; Aged; Artificial Intelligence; Humans; Hypertension; Telemedicine
Publisher
WILEY
Type
journal article