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  • Advanced method used for hypertension’s risk factors stratification: support vector machines and gravitational search algorithm

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    Author(s)
    Khosravi, Alireza
    Gharipour, Amin
    Gharipour, Mojgan
    Khosravi, Mohammadreza
    Andalib, Elham
    Shirani, Shahin
    Mirmohammadsedeghi, Mohsen
    Griffith University Author(s)
    Gharipour, Amin
    Year published
    2015
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    Abstract
    BACKGROUND: The aim of this study is to present an objective method based on support vector machines (SVMs) and gravitational search algorithm (GSA) which is initially utilized for recognition the pattern among risk factors and hypertension (HTN) to stratify and analysis HTN’s risk factors in an Iranian urban population. METHODS: This community-based and cross-sectional research has been designed based on the probabilistic sample of residents of Isfahan, Iran, aged 19 years or over from 2001 to 2007. One of the household members was randomly selected from different age groups. Selected individuals were invited to a predefined ...
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    BACKGROUND: The aim of this study is to present an objective method based on support vector machines (SVMs) and gravitational search algorithm (GSA) which is initially utilized for recognition the pattern among risk factors and hypertension (HTN) to stratify and analysis HTN’s risk factors in an Iranian urban population. METHODS: This community-based and cross-sectional research has been designed based on the probabilistic sample of residents of Isfahan, Iran, aged 19 years or over from 2001 to 2007. One of the household members was randomly selected from different age groups. Selected individuals were invited to a predefined health center to be educated on how to collect 24-hour urine sample as well as learning about topographic parameters and blood pressure measurement. The data from both the estimated and measured blood pressure [for both systolic blood pressure (SBP) and diastolic blood pressure (DBP)] demonstrated that optimized SVMs have a highest estimation potential. RESULTS: This result was particularly more evident when SVMs performance is evaluated with regression and generalized linear modeling (GLM) as common methods. Blood pressure risk factors impact analysis shows that age has the highest impact level on SBP while it falls second on the impact level ranking on DBP. The results also showed that body mass index (BMI) falls first on the impact level ranking on DBP while have a lower impact on SBP. CONCLUSION: Our analysis suggests that salt intake could efficiently influence both DBP and SBP with greater impact level on SBP. Therefore, controlling salt intake may lead to not only control of HTN but also its prevention.
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    Journal Title
    ARYA Atherosclerosis
    Volume
    11
    Issue
    6
    Publisher URI
    http://arya.mui.ac.ir/index.php/arya/article/view/1066
    Copyright Statement
    © The Author(s) 2015. This is an Open Access article distributed under the terms of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Subject
    Cardiovascular medicine and haematology
    Clinical sciences not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/141474
    Collection
    • Journal articles

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