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  • Review Article
  • Review Series - Digital Hypertension
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Future possibilities for artificial intelligence in the practical management of hypertension

Hypertension Research volume 43, pages 1327–1337 (2020)Cite this article

Abstract

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.

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Acknowledgements

Hiroshi Koshimizu would like to express my gratitude to Omron Healthcare Co., Ltd. for giving me the time to complete this work.

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  1. Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan

    Hiroshi Koshimizu, Ryosuke Kojima & Yasushi Okuno

  2. Development Center, Omron Healthcare Co., Ltd., Kyoto, 617-0002, Japan

    Hiroshi Koshimizu

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Koshimizu, H., Kojima, R. & Okuno, Y. Future possibilities for artificial intelligence in the practical management of hypertension. Hypertens Res 43, 1327–1337 (2020). https://doi.org/10.1038/s41440-020-0498-x

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