Tsoi, KelvinKelvinTsoiYiu, KarenKarenYiuLee, HelenHelenLeeCheng, Hao-MinHao-MinChengTZUNG-DAU WANGTay, Jam-ChinJam-ChinTayTeo, Boon WeeBoon WeeTeoTurana, YudaYudaTuranaSoenarta, Arieska AnnArieska AnnSoenartaSogunuru, Guru PrasadGuru PrasadSogunuruSiddique, SaulatSaulatSiddiqueChia, Yook-ChinYook-ChinChiaShin, JinhoJinhoShinChen, Chen-HuanChen-HuanChenWang, Ji-GuangJi-GuangWangKario, KazuomiKazuomiKario2022-01-212022-01-212021-031524-6175https://scholars.lib.ntu.edu.tw/handle/123456789/592778The 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.en[SDGs]SDG3antihypertensive 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; Telemedicinejournal article10.1111/jch.14180335335362-s2.0-85100377966WOS:000614156700001https://scholars.lib.ntu.edu.tw/handle/123456789/550042