Future possibilities for artificial intelligence in the practical management of hypertension

被引:18
|
作者
Koshimizu, Hiroshi [1 ,2 ]
Kojima, Ryosuke [1 ]
Okuno, Yasushi [1 ]
机构
[1] Kyoto Univ, Grad Sch Med, Dept Biomed Data Intelligence, Kyoto 6068507, Japan
[2] Omron Healthcare Co Ltd, Dev Ctr, Kyoto 6170002, Japan
关键词
Artificial intelligence; Machine learning; Blood pressure management; Blood pressure measurement; Blood pressure prediction; BLOOD-PRESSURE; CARDIOVASCULAR-DISEASE; CLINICAL-TRIAL; RISK; VARIABILITY; PREVENTION; REDUCTION; ACCURACY; GLUCOSE; AGE;
D O I
10.1038/s41440-020-0498-x
中图分类号
R6 [外科学];
学科分类号
1002 ; 100210 ;
摘要
The use of artificial intelligence in numerous prediction and classification tasks, including clinical research and healthcare management, is becoming increasingly more common. This review describes the current status and a future possibility for artificial intelligence in blood pressure management, that is, the possibility of accurately predicting and estimating blood pressure using large-scale data, such as personal health records and electronic medical records. Individual blood pressure continuously changes because of lifestyle habits and the environment. This review focuses on two topics regarding controlling changing blood pressure: a novel blood pressure measurement system and blood pressure analysis using artificial intelligence. Regarding the novel blood pressure measurement system, we compare the conventional cuff-less method with the analysis of pulse waves using artificial intelligence for blood pressure estimation. Then, we describe the prediction of future blood pressure values using machine learning and deep learning. In addition, we summarize factor analysis using "explainable AI" to solve a black-box problem of artificial intelligence. Overall, we show that artificial intelligence is advantageous for hypertension management and can be used to establish clinical evidence for the practical management of hypertension.
引用
收藏
页码:1327 / 1337
页数:11
相关论文
共 50 条
  • [1] Future possibilities for artificial intelligence in the practical management of hypertension
    Hiroshi Koshimizu
    Ryosuke Kojima
    Yasushi Okuno
    Hypertension Research, 2020, 43 : 1327 - 1337
  • [2] Practical Reason vs. Artificial Intelligence: The Future of Business Management
    Murcio Rodriguez, Ricardo
    Scalzo, German
    Llaguno Sanudo, Jorge
    REVISTA EMPRESA Y HUMANISMO, 2020, 23 (01) : 65 - 86
  • [3] THE POSSIBILITIES OF ARTIFICIAL-INTELLIGENCE IN THE OFFICE OF THE FUTURE
    ZELEWSKI, S
    BETRIEBSWIRTSCHAFTLICHE FORSCHUNG UND PRAXIS, 1989, 41 (02): : 177 - 188
  • [4] The practical applications of artificial intelligence and the future of ViEW
    Kato K.
    Nishiyama M.
    Kawanishi R.
    Kataoka H.
    Seimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering, 2021, 87 (10): : 783 - 786
  • [5] Artificial intelligence in medicine: current trends and future possibilities
    Buch, Varun H.
    Ahmed, Irfan
    Maruthappu, Mahiben
    BRITISH JOURNAL OF GENERAL PRACTICE, 2018, 68 (668): : 143 - 144
  • [6] 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
    JOURNAL OF CLINICAL HYPERTENSION, 2021, 23 (03): : 568 - 574
  • [7] Artificial Intelligence in Public Health: Current Trends and Future Possibilities
    Giansanti, Daniele
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (19)
  • [8] Artificial intelligence in bladder cancer: current trends and future possibilities
    Ma Jun
    Vaishnani Deep K.
    Lin Rixu
    Lyu Jiayu
    Ni Bingyan
    Zhang Yang
    Hu Mengjun
    Chen Guorong
    中华医学杂志英文版, 2022, 135 (07) : 881 - 882
  • [9] Artificial intelligence in bladder cancer: current trends and future possibilities
    Ma, Jun
    Vaishnani, Deep K.
    Lin, Rixu
    Lyu, Jiayu
    Ni, Bingyan
    Zhang, Yang
    Hu, Mengjun
    Chen, Guorong
    CHINESE MEDICAL JOURNAL, 2022, 135 (07) : 881 - 882
  • [10] Artificial Intelligence and Hypertension: Recent Advances and Future Outlook
    Chaikijurajai, Thanat
    Laffin, Luke J.
    Tang, Wai Hong Wilson
    AMERICAN JOURNAL OF HYPERTENSION, 2020, 33 (11) : 967 - 974