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A neuro-fuzzy-classifier for a knowledge-based glaucoma monitor

  • Gudrun Zahlmann
  • Matthias Scherf
  • Aharon Wegner
Probabilistic Models and Fuzzy Logic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1211)

Abstract

A knowledge-based glaucoma monitor is developed to detect critical or suspicious situations in patient's ophthalmic data sets. The decision, which type of situation occurs is made by a neuro-fuzzy classifier. The neural net part is based on a special developed feature selection algorithm and a RBF network. Fuzzy classification is realised by a fuzzy rule set combining all patient data with the classification results of the neural net classifier to the final decision.

Keywords

Fuzzy Rule Feature Selection Technique Neural Network Classifier Situation Class Artificial Neural Network Classifier 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Gudrun Zahlmann
    • 1
  • Matthias Scherf
    • 1
  • Aharon Wegner
    • 2
  1. 1.GSF, National Research Center for Environment and HealthInstitute of Medical Informatics and Health Services ResearchNeuherberg
  2. 2.Department of Ophthalmology, Clinic rechts der IsarTechnical University of MunichMunich

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