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Individual prognosis of diabetes long-term risks: a CBR approach
E Armengol1, A Palaudàries, E Plaza
1Artificial Intelligence Research Institute (IIIA-CSIC), Campus UAB, Bellaterra, Catalonia, Spain. eva@iiia.csic.es
Methods of Information in Medicine
|April 20, 2001
Abstract:
We present DIRAS, an application to support physicians in determining the risk of complications for individual diabetic patients. The risk pattern of each diabetic patient is obtained using a Case-based Reasoning method called LID. Case-based Reasoning is an Artificial Intelligence technique based on solving new situations according to past experiences. For each patient, the LID method determines the risk of each diabetic complication according to the risk of already diagnosed patients. In addition, LID builds a description that can be viewed as an explanation of the obtained risk.