ArticleIEEE access : practical innovations, open solutions
Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Linear Analysis.
Article in IEEE access : practical innovations, open solutions. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Quantification of dynamic cerebral autoregulation and COJournal of applied physiology (Bethesda, Md. : 1985) · 2020Article
- Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Nonlinear Analysis.IEEE transactions on bio-medical engineering · 2017Article
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Authors and funding
4 authors.
Funding
Abstract
Compartmental and data-based modeling of cerebral hemodynamics are alternative approaches that utilize distinct model forms and have been employed in the quantitative study of cerebral hemodynamics. This paper examines the relation between a compartmental equivalent-circuit and a data-based input-output model of dynamic cerebral autoregulation (DCA) and CO2-vasomotor reactivity (DVR). The compartmental model is constructed as an equivalent-circuit utilizing putative first principles and previously proposed hypothesis-based models. The linear input-output dynamics of this compartmental model are compared with data-based estimates of the DCA-DVR process. This comparative study indicates that there are some qualitative similarities between the two-input compartmental model and experimental results.
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Registered trials
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