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
fDate :
March 31 2008-April 4 2008
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;
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
DOI :
10.1109/AICCSA.2008.4493641