A Comprehensive Analysis of Hypertension Disease Risk-Factors, Diagnostics, and Detections Using Deep Learning-Based Approaches
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s11831-023-10035-w.pdf
Reference49 articles.
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2. Parati G et al (2021) Home blood pressure monitoring: methodology, clinical relevance and practical application: a 2021 position paper by the Working Group on Blood Pressure Monitoring and Cardiovascular Variability of the European Society of Hypertension. J Hypertens 39(9):1742–1767. https://doi.org/10.1097/hjh.0000000000002922
3. Topol EJ (2019) High-performance medicine: the convergence of human and artificial intelligence. Nat Med 25(1):44–56. https://doi.org/10.1038/s41591-018-0300-7
4. Beaney T et al (2019) May Measurement Month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension. Eur Heart J 40(25):2006–2017. https://doi.org/10.1093/eurheartj/ehz300
5. Krum H, Jelinek MV, Stewart S, Sindone A, Atherton JJ, Hawkes AL (2006) Guidelines for the prevention, detection and management of people with chronic heart failure in Australia 2006. Med J Aust 185(10):549–556. https://doi.org/10.5694/j.1326-5377.2006.tb00690.x
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