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Intelligent Data Analysis in Medicine and Pharmacology

  • Nada Lavrač
  • Elpida T. Keravnou
  • Blaž Zupan

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Intelligent Data Analysis In Medicine And Pharmacology: An Overview

    1. Nada Lavrač, Elpida T. Keravnou, Blaž Zupan
      Pages 1-13
  3. Data Abstraction

    1. Front Matter
      Pages 15-15
    2. Silvia Miksch, Werner Horn, Christian Popow, Franz Paky
      Pages 17-36
    3. Riccardo Bellazzi, Cristiana Larizza, Alberto Riva
      Pages 81-98
    4. Marko Bohanec, Miran Rems, Smiljana Slavec, Božo Urh
      Pages 99-111
  4. Data Mining

    1. Front Matter
      Pages 113-113
    2. Matjaž Kukar, Nikola Bešič, Igor Kononenko, Marija Auersperg, Marko Robnik-Šikonja
      Pages 115-129
    3. Iztok A. Pilih, Dunja Mladenić, Nada Lavrač, Tine S. Prevec
      Pages 131-148
    4. William R. Shankle, Subramani Mani, Michael J. Pazzani, Padhraic Smyth
      Pages 149-165
    5. Branko Šter, Matjaž Kukar, Andrej Dobnikar, Igor Kranjec, Igor Kononenko
      Pages 167-185
    6. Nada Lavrač, Dragan Gamberger, Sašo Džeroski
      Pages 187-205
    7. Sašo Džeroski, Steffen Schulze-Kremer, Karsten R. Heidtke, Karsten Siems, Dietrich Wettschereck
      Pages 207-225
    8. Fumio Mizoguchi, Hayato Ohwada, Makiko Daidoji, Shiroaki Shirato
      Pages 227-242
    9. Ashwin Srinivasan, Ross D. King, Stephen H. Muggleton, Michael J. E. Sternberg
      Pages 243-260
    10. Blaž Zupan, John A. Halter, Marko Bohanec
      Pages 261-278
    11. Udo Heuser, Josef Göppert, Wolfgang Rosenstiel, Andreas Stevens
      Pages 279-294
    12. Michael W. Kattan, Haku Ishida, Peter T. Scardino, J. Robert Beck
      Pages 295-306
  5. Back Matter
    Pages 307-310

About this book

Introduction

Intelligent data analysis, data mining and knowledge discovery in databases have recently gained the attention of a large number of researchers and practitioners. This is witnessed by the rapidly increasing number of submissions and participants at related conferences and workshops, by the emergence of new journals in this area (e.g., Data Mining and Knowledge Discovery, Intelligent Data Analysis, etc.), and by the increasing number of new applications in this field. In our view, the awareness of these challenging research fields and emerging technologies has been much larger in industry than in medicine and pharmacology. The main purpose of this book is to present the various techniques and methods that are available for intelligent data analysis in medicine and pharmacology, and to present case studies of their application.
Intelligent Data Analysis in Medicine and Pharmacology consists of selected (and thoroughly revised) papers presented at the First International Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-96) held in Budapest in August 1996 as part of the 12th European Conference on Artificial Intelligence (ECAI-96), IDAMAP-96 was organized with the motivation to gather scientists and practitioners interested in computational data analysis methods applied to medicine and pharmacology, aimed at narrowing the increasing gap between excessive amounts of data stored in medical and pharmacological databases on the one hand, and the interpretation, understanding and effective use of stored data on the other hand. Besides the revised Workshop papers, the book contains a selection of contributions by invited authors.
The expected readership of the book is researchers and practitioners interested in intelligent data analysis, data mining, and knowledge discovery in databases, particularly those who are interested in using these technologies in medicine and pharmacology. Researchers and students in artificial intelligence and statistics should find this book of interest as well. Finally, much of the presented material will be interesting to physicians and pharmacologists challenged by new computational technologies, or simply in need of effectively utilizing the overwhelming volumes of data collected as a result of improved computer support in their daily professional practice.

Keywords

Monitor artificial intelligence classification data analysis data mining database intelligence knowledge discovery learning machine learning physiology programming statistics therapy

Editors and affiliations

  • Nada Lavrač
    • 1
  • Elpida T. Keravnou
    • 2
  • Blaž Zupan
    • 1
  1. 1.J. Stefan InstituteLjubljanaSlovenia
  2. 2.University of CyprusNicosiaCyprus

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-6059-3
  • Copyright Information Kluwer Academic Publishers 1997
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-7775-7
  • Online ISBN 978-1-4615-6059-3
  • Series Print ISSN 0893-3405
  • Buy this book on publisher's site