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Case-Based Reasoning Systems for Medical Applications with Improved Adaptation and Recovery Stages

  • X. Blanco Valencia
  • D. Bastidas Torres
  • C. Piñeros Rodriguez
  • D. H. Peluffo-Ordóñez
  • M. A. Becerra
  • A. E. Castro-Ospina
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10813)

Abstract

Case-Based Reasoning Systems (CBR) are in constant evolution, as a result, this article proposes improving the retrieve and adaption stages through a different approach. A series of experiments were made, divided in three sections: a proper pre-processing technique, a cascade classification, and a probability estimation procedure. Every stage offers an improvement, a better data representation, a more efficient classification, and a more precise probability estimation provided by a Support Vector Machine (SVM) estimator regarding more common approaches. Concluding, more complex techniques for classification and probability estimation are possible, improving CBR systems performance due to lower classification error in general cases.

Keywords

Case-based reasoning Preprocessing Cascade classification Probability 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Universidad de SalamancaSalamancaSpain
  2. 2.Universidad de NariñoPastoColombia
  3. 3.Universidad Yachay TechUrcuquíEcuador
  4. 4.Instituto Tecnológico MetropolitanoMedellínColombia

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