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Applications of artificial intelligence for hypertension management

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 ar...

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Autores principales: Tsoi, Kelvin, Yiu, Karen, Lee, Helen, Cheng, Hao‐Min, Wang, Tzung‐Dau, 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8029548/
https://www.ncbi.nlm.nih.gov/pubmed/33533536
http://dx.doi.org/10.1111/jch.14180
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author Tsoi, Kelvin
Yiu, Karen
Lee, Helen
Cheng, Hao‐Min
Wang, Tzung‐Dau
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
author_facet Tsoi, Kelvin
Yiu, Karen
Lee, Helen
Cheng, Hao‐Min
Wang, Tzung‐Dau
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
author_sort Tsoi, Kelvin
collection PubMed
description 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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spelling pubmed-80295482021-12-16 Applications of artificial intelligence for hypertension management Tsoi, Kelvin Yiu, Karen Lee, Helen Cheng, Hao‐Min Wang, Tzung‐Dau 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 J Clin Hypertens (Greenwich) Treatment and Management of Hypertension 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. John Wiley and Sons Inc. 2021-02-03 /pmc/articles/PMC8029548/ /pubmed/33533536 http://dx.doi.org/10.1111/jch.14180 Text en © 2021 The Authors. The Journal of Clinical Hypertension published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Treatment and Management of Hypertension
Tsoi, Kelvin
Yiu, Karen
Lee, Helen
Cheng, Hao‐Min
Wang, Tzung‐Dau
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
Applications of artificial intelligence for hypertension management
title Applications of artificial intelligence for hypertension management
title_full Applications of artificial intelligence for hypertension management
title_fullStr Applications of artificial intelligence for hypertension management
title_full_unstemmed Applications of artificial intelligence for hypertension management
title_short Applications of artificial intelligence for hypertension management
title_sort applications of artificial intelligence for hypertension management
topic Treatment and Management of Hypertension
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8029548/
https://www.ncbi.nlm.nih.gov/pubmed/33533536
http://dx.doi.org/10.1111/jch.14180
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