Modeling the adaptive pathophysiology of essential hypertension. | |
MedLine Citation:
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PMID: 22254488 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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This paper proposes an adaptive neuro-fuzzy model to study the pathophysiology of essential hypertension. Using diverse inputs such as risk factors, physical relations and medical interventions, and states that include both transient and resting states for key physiological variables (blood pressure, total peripheral resistance), it can roughly predict both real-time and long-term blood pressure change for a robust range of inputs. Although it was tuned using published population data, it can be applied to specific individuals to estimate the risks of hypertension with different life experience. |
Authors:
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Yu Wang; Jack M Winters |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference Volume: 2011 ISSN: 1557-170X ISO Abbreviation: Conf Proc IEEE Eng Med Biol Soc Publication Date: 2011 |
Date Detail:
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Created Date: 2012-01-18 Completed Date: 2012-06-07 Revised Date: 2014-08-21 |
Medline Journal Info:
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Nlm Unique ID: 101243413 Medline TA: Conf Proc IEEE Eng Med Biol Soc Country: United States |
Other Details:
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Languages: eng Pagination: 1029-32 Citation Subset: IM |
Export Citation:
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MeSH Terms | |
Descriptor/Qualifier:
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Adaptation, Physiological Arteries / physiopathology* Blood Flow Velocity Blood Pressure Computer Simulation Humans Hypertension / physiopathology* Models, Cardiovascular* Vascular Resistance |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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