Alison J. Brown’s research while affiliated with University of Mississippi Medical Center and other places

What is this page?


This page lists works of an author who doesn't have a ResearchGate profile or hasn't added the works to their profile yet. It is automatically generated from public (personal) data to further our legitimate goal of comprehensive and accurate scientific recordkeeping. If you are this author and want this page removed, please let us know.

Publications (1)


(A) The XML code used to describe a curve function. Xm is an X value, Ym is the associated Y value, and Sm is the slope of the curve at the Xm, Ym data point. (B) This demonstrates how the curve function is called in the XML code. “Variable name” is the output value returned following evaluation of the curve function at a given input value. (C) Describes the relationship between blood glucose and insulin release. (D) Shows the sigmoid fit based on the X, Y, and slope data presented in (C).
The Model Navigator is used to understand the physiological interactions and the documentation of HumMod. The left side panels list all of the variables in HumMod. The Center panels describe the interactions between each variable. The right panel shows the file location where a variable is defined.
This Figure provides an example of how the Model Navigator displays the background documentation. The “Docs” tab on the center panel of the Model Navigator is selected. In this example the right panel displays an overview of erythropoietin.
This figure provides an example of the ability of HumMod to simulate time dependent physiological responses. In this example the “person” is initially lying down for 10 min, then stands for 10 min, followed by 30 min of exercise.
This figure demonstrates the cardiac output and blood flow responses before and during the exercise period shown in Figure 4.

+3

HumMod: A Modeling Environment for the Simulation of Integrative Human Physiology
  • Article
  • Full-text available

April 2011

·

2,851 Reads

·

154 Citations

·

Alison J. Brown

·

Leland Husband

·

[...]

·

Thomas G. Coleman

Mathematical models and simulations are important tools in discovering key causal relationships governing physiological processes. Simulations guide and improve outcomes of medical interventions involving complex physiology. We developed HumMod, a Windows-based model of integrative human physiology. HumMod consists of 5000 variables describing cardiovascular, respiratory, renal, neural, endocrine, skeletal muscle, and metabolic physiology. The model is constructed from empirical data obtained from peer-reviewed physiological literature. All model details, including variables, parameters, and quantitative relationships, are described in Extensible Markup Language (XML) files. The executable (HumMod.exe) parses the XML and displays the results of the physiological simulations. The XML description of physiology in HumMod's modeling environment allows investigators to add detailed descriptions of human physiology to test new concepts. Additional or revised XML content is parsed and incorporated into the model. The model accurately predicts both qualitative and quantitative changes in clinical and experimental responses. The model is useful in understanding proposed physiological mechanisms and physiological interactions that are not evident, allowing one to observe higher level emergent properties of the complex physiological systems. HumMod has many uses, for instance, analysis of renal control of blood pressure, central role of the liver in creating and maintaining insulin resistance, and mechanisms causing orthostatic hypotension in astronauts. Users simulate different physiological and pathophysiological situations by interactively altering numerical parameters and viewing time-dependent responses. HumMod provides a modeling environment to understand the complex interactions of integrative physiology. HumMod can be downloaded at http://hummod.org

Download

Citations (1)


... A negative relationship between trialability and the adoption of cryptocurrency suggests that the fewer opportunities individuals have to try and familiarize themselves with cryptocurrency, the less likely they are to adopt it as a digital currency. This supports the findings of Hester et al., (2011) but conflicts with the conclusions of Wang and Wang (2016), Rhein (2021), Schuwer and Janssen (2018), and Nazari et al. (2017). This is logical because adopters may not need to extensively examine all available resources for a short period of time. ...

Reference:

Customer-Centric Value Assessment of Cryptocurrency Adaptation
HumMod: A Modeling Environment for the Simulation of Integrative Human Physiology