Applications of artificial intelligence for hypertension management

  • Tsoi, Kelvin
  • Yiu, Karen
  • Lee, Helen
  • Cheng, Hao-Min
  • Wang, Tzung-Dau
  • ... Shin, Jinho
  • 외 10명
Citations

WEB OF SCIENCE

49
Citations

SCOPUS

74

초록

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.

키워드

antihypertensive agentantihypertensive therapyartificial intelligenceblood pressure monitoringblood pressure regulationdisease burdenfeasibility studyhealth care costhumanhypertensionincidencelifestyle modificationmobile applicationoutcome assessmentpredictionprognosisReviewtelemedicinetrend studyvalidation processagedartificial intelligencehypertensiontelemedicine
제목
Applications of artificial intelligence for hypertension management
저자
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
DOI
10.1111/jch.14180
발행일
2021-03
유형
Review; Early Access
저널명
Journal of Clinical Hypertension
23
3
페이지
568 ~ 574

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