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A Hybrid CBR and BN Architecture Refined through Data Analysis Tore Bruland
 

Summary: A Hybrid CBR and BN Architecture Refined through Data Analysis
Tore Bruland
Norwegian University of Science and Technology
Department of Cancer Research and Molecular Medicine
Trondheim, Norway
torebrul@idi.ntnu.no
Agnar Aamodt, Helge Langseth
Norwegian University of Science and Technology
Department of Computer and Information Science
Trondheim, Norway
agnar@idi.ntnu.no, helgel@idi.ntnu.no
Abstract--The overall goal of this research is to study rea-
soning under uncertainty by combining Bayesian Networks and
Case-Based Reasoning through constructing an experimental
decision support system for classification of cancer pain. We
have experimentally analysed a medical dataset in order to
reveal properties of the data with respect to properties of
the two reasoning methods. We also preprocessed our medical
data with help from a clinical expert, which resulted in four
data sets with different characteristics. This culminates in a

  

Source: Aamodt, Agnar - Department of Computer and Information Science, Norwegian University of Science and Technology

 

Collections: Computer Technologies and Information Sciences