Medical Data Analysis

First International Symposium, ISMDA 2000 Frankfurt, Germany, September 29–30, 2000 Proceedings

  • Rüdiger W. Brause
  • Ernst Hanisch
Conference proceedings ISMDA 2000

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1933)

Table of contents

  1. Front Matter
    Pages I-XI
  2. Keynote Lectures

    1. T. Wetter
      Pages 1-3
    2. Basilio Sierra, Iñaki Inza, Pedro Larrañaga
      Pages 4-14
    3. Victor Maojo, José Sanandrés
      Pages 17-22
  3. Time Series Analysis

    1. Rainer Schmidt, Lothar Gierl
      Pages 23-33
    2. Aleš Černošek, Vladimir Krajča, Jitka Mohylová, Svojmil Petránek, Miloš Matoušek, Karel Paul
      Pages 34-42
    3. Gerhard Staude, Werner Wolf
      Pages 43-48
    4. Axel Wismüller, Dominik R. Dersch, Bernadette Lipinski, Klaus Hahn, Dorothee Auer
      Pages 49-54
    5. T. Müller, T. Ball, R. Kristeva-Feige, Th. Mergner, J. Timmer
      Pages 55-60
    6. Holger Steltner, Richard Staats, Michael Vogel, Christian Virchow, Heinrich Matthys, Josef Guttmann et al.
      Pages 61-66
    7. Roland Fried, Ursula Gather, Michael Imhoff, Marcus Bauer
      Pages 67-77
    8. Niels Wessel, Agnes Schumann, Alexander Schirdewan, Andreas Voss, Jürgen Kurths
      Pages 78-87
    9. Laura Cimponeriu, Anastassios Bezerianos
      Pages 88-96
  4. Bayes Networks

    1. Iñaki Inza, Marisa Merino, Pedro Larranaga, Jorge Quiroga, Basilio Sierra, Marcos Girala
      Pages 97-110
    2. Carmen Lacave, Roberto Atienza, Francisco J. Diez
      Pages 122-129
  5. Neural Nets

    1. Jürgen Paetz, Fred Hamker, Sven Thöne
      Pages 130-137
    2. Thomas Villmann, Wieland Hermann, Michael Geyer
      Pages 138-151
    3. Werner Horbelt, Thorsten Müller, Jens Timmer, Werner Melzer, Karl Winkler
      Pages 152-159

About these proceedings

Introduction

It is a pleasure for us to present the contributions of the First International Symposium on Medical Data Analysis. Traditionally, the eld of medical data analysis can be devided into classical topics such as medical statistics, sur- val analysis, biometrics and medical informatics. Recently, however, time series analysis by physicists, machine learning and data mining with methods such as neural networks, Bayes networks or fuzzy computing by computer scientists have contributed important ideas to the led of medical data analysis. Although all these groups have similar intentions, there was nearly no exchange or discussion between them. With the growing possibilities for storing and ana- zing patient data, even in smaller health care institutions, the need for a rational treatment of all these data emerged as well. Therefore, the need for data exchange and presentation systems grew also. The goal of the symposium is to collect all these relevant aspects together. It provides an international forum for the sharing and exchange of original re- arch results, ideas and practical experiences among researchers and application developers from di erent areas related to medical applications dealing with the analysis of medical data. After a thorough reviewing process, 33 high quality papers were selected from the 45 international submissions. These contributions provided the di erent - pects of the eld in order to represent us with an exciting program.

Keywords

Analysis Bayesian network algorithms data analysis data mining fuzzy learning machine learning medical informatics modeling neural network

Editors and affiliations

  • Rüdiger W. Brause
    • 1
  • Ernst Hanisch
    • 2
  1. 1.Fachbereich Biologie und Informatik AG Adaptive SystemarchitekturJohann Wolfgang Goethe-UniversitätFrankfurt a.M.Germany
  2. 2.Klinik für Allgemein- und GefässchirurgieJohann Wolfgang Goethe-UniversitätFrankfurt a.M.Germany

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-39949-6
  • Copyright Information Springer-Verlag Berlin Heidelberg 2000
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-41089-8
  • Online ISBN 978-3-540-39949-0
  • Series Print ISSN 0302-9743
  • About this book