• DocumentCode
    3301215
  • Title

    Intelligent Diabetes Assistant: Using machine learning to help manage diabetes

  • Author

    Duke, David L. ; Thorpe, Charles ; Mahmoud, Mazahir ; Zirie, Mahmoud

  • Author_Institution
    Carnegie Mellon Univ.-Qatar Campus, Doha
  • fYear
    2008
  • fDate
    March 31 2008-April 4 2008
  • Firstpage
    913
  • Lastpage
    914
  • Abstract
    We believe that machine learning can be used to help diabetics and care providers manage diabetes by predicting the effect that behaviors have on blood glucose. This when coupled with telemedicine could help care providers provide better individualized therapy more frequently. Currently, diabetics might get 15 minutes of interaction with a health expert during a checkup, and in that amount of time the physician must quickly evaluate the patient´s health to offer therapy advice. The Intelligent Diabetes Assistant (IDA) addresses this problem by remotely collecting data, instantaneously sharing that data with a physician, and automatically processing the data to reveal important patterns. The system makes data collection more efficient for the patient, and it will make data analysis more efficient for the care team. We have conducted a two week longitudinal study tracking the lifestyle, nutrition, and blood glucose readings of 10 diabetics using IDA.
  • Keywords
    biomedical education; computer based training; data analysis; diseases; health care; learning (artificial intelligence); medical computing; telemedicine; biomedical education; blood glucose; data analysis; health care; intelligent diabetes assistant; machine learning; telemedicine; Biomedical imaging; Blood; Data analysis; Diabetes; Displays; Learning systems; Machine learning; Medical treatment; Sugar; Telemedicine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Systems and Applications, 2008. AICCSA 2008. IEEE/ACS International Conference on
  • Conference_Location
    Doha
  • Print_ISBN
    978-1-4244-1967-8
  • Electronic_ISBN
    978-1-4244-1968-5
  • Type

    conf

  • DOI
    10.1109/AICCSA.2008.4493641
  • Filename
    4493641