A hybrid machine learning approach for hypertension risk prediction
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-021-06060-0.pdf
Reference30 articles.
1. Mills KT, Bundy JD, Kelly TN, Reed JE, Kearney PM (2016) Global disparities of hypertension prevalence and control: a systematic analysis of population-based studies from 90 countries. Circulation 134(6):441–450
2. Liu L (2019) 2018 Chinese guidelines for the management of hypertension. Chin J Cardiovasc Med 24:24–56
3. Liu L (2011) Writing group of Chinese guidelines for the management of H: 2010 Chinese guidelines for the management of hypertension [Article in Chinese]. Zhonghua xin xue guan bing za zhi 39:579–615. https://doi.org/10.1038/cdd.2010.68
4. Chen ShuTang (1999) Prevention of hypertension [Article in Chinese]. China Healthcare & Nutrition 10:26–27. https://doi.org/CNKI:SUN:ZHBJ.0.1999-10-018
5. Boudabsa L, Filipovic D (2020) Machine learning with kernels for portfolio valuation and risk management, Papers, arXiv:1906.03726. https://EconPapers.repec.org/RePEc:arx:papers:1906.03726
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