Artificial Neural Networks in Medicine and Biology

Proceedings of the ANNIMAB-1 Conference, Göteborg, Sweden, 13–16 May 2000

ISBN: 978-1-85233-289-1 (Print) 978-1-4471-0513-8 (Online)

Table of contents (50 chapters)

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  1. Front Matter

    Pages I-XII

  2. Invited Presentations

    1. Front Matter

      Pages 1-1

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      Pages 3-9

      Protein β-Sheet Partner Prediction by Neural Networks

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      Pages 10-17

      ART Neural Networks for Medical Data Analysis and Fast Distributed Learning

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      Pages 18-25

      Modelling Uncertainty in Biomedical Applications of Neural Networks

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      Pages 26-36

      Neural Computation in Medicine: Perspectives and Prospects

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      Pages 37-44

      Discriminating Gourmets, Lovers, and Enophiles? Neural Nets Tell All About Locusts, Toads, and Roaches

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      Pages 45-53

      An Unsupervised Learning Method that Produces Organized Representations from Real Information

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      Pages 54-62

      On Forgetful Attractor Network Memories

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      Pages 63-71

      Outstanding Issues for Clinical Decision Support with Neural Networks

  3. Medical Image Analysis

    1. Front Matter

      Pages 73-73

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      Pages 75-80

      Cancerous Liver Tissue Differentiation Using LVQ

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      Pages 81-86

      Quantification of Diabetic Retinopathy using Neural Networks and Sensitivity Analysis

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      Pages 87-92

      Internet Based Artificial Neural Networks for the Interpretation of Medical Images

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      Pages 93-98

      Segmentation of Magnetic Resonance Images According to Contrast Agent Uptake Kinetics Using a Competitive Neural Network

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      Pages 99-104

      Applications of Optimizing Neural Networks in Medical Image Registration

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      Pages 105-110

      A Learning by Sample Approach for the Detection of Features in Medical Images.

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      Pages 111-116

      Neural Network Based Classification of Cell Images via Estimation of Fractal Dimensions

  4. Signal Processing in Medicine

    1. Front Matter

      Pages 117-117

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      Pages 119-124

      Mutual Control Neural Networks for Sleep Arousal Detection

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      Pages 125-130

      Extraction of Sleep-Spindles from the Electroencephalogram (EEG)

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      Pages 131-136

      Analyzing Brain Tumor related EEG Signals with ICA Algorithms

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      Pages 137-142

      Isolating Seizure Activity in the EEG with Independent Component Analysis

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      Pages 143-148

      Seizure Detection with the Self-Organising Feature Map

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