• DocumentCode
    2809088
  • Title

    An Agent Model of a Diabetic Patient

  • Author

    Nejad, Sara Ghoreishi ; Paranjape, Raman

  • Author_Institution
    Univ. of Regina, Regina
  • fYear
    2007
  • fDate
    22-26 April 2007
  • Firstpage
    214
  • Lastpage
    218
  • Abstract
    This paper presents a new paradigm for modeling illness in the human population. In this work we propose the development of a patient model using a Mobile Software Agent. We concentrate on Diabetes Mellitus because of the prevalence of this disease and the reality that many citizens must learn to manage their disease through some simple guidelines on their diet, exercise and medication. This form of modeling illness has the potential to predict outcomes for diabetic patients depending on their lifestyle. We further believe that the Patient Agent could be an effective tool in assisting patients to understand their prognosis if they are not meticulous in controlling their blood sugar and insulin levels. The Patient Agent is developed in accordance with the general parameters used in archetypal Diabetes medical tests. Conventional formulae have been applied to transform input variables such as Food, Exercise, and Medications, as well as other risk factors like Age, Ethnicity, and Gender, into output variables such as Blood Glucose and Blood Pressure. The time evolution of the Patient Agent is represented through the outputs which deteriorate over the long term period.
  • Keywords
    diseases; medical computing; mobile agents; patient monitoring; software agents; archetypal diabetes medical tests; blood sugar levels; diabetic patient; illness modeling; insulin levels; mobile software agent; Blood; Diabetes; Diseases; Guidelines; Humans; Input variables; Insulin; Medical tests; Predictive models; Software agents;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering, 2007. CCECE 2007. Canadian Conference on
  • Conference_Location
    Vancouver, BC
  • ISSN
    0840-7789
  • Print_ISBN
    1-4244-1020-7
  • Electronic_ISBN
    0840-7789
  • Type

    conf

  • DOI
    10.1109/CCECE.2007.59
  • Filename
    4232718