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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

State-of-the-Art and Future Challenges

  • Book
  • © 2014

Overview

Editors:
  1. Andreas Holzinger

    1. Research Unit Human-Computer Interaction, Austrian IBM Watson Think Gruop, Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria

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  2. Igor Jurisica

    1. IBM Life Sciences Discovery Centre, TECHNA for the Advancement of Technology for Health, Princess Margaret Cancer Centre, University Health Network, Toronto, Canada

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  • Focuses on hot topics from interactive knowledge discovery and data mining in biomedical informatics
  • Each paper describes the state-of-the-art and focuses on open problems and future challenges in order to provide a research agenda to stimulate further research and progress
  • Written by professionals from diverse areas with various backgrounds who share a common vision: making sense of complex data

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 8401)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

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Table of contents (19 chapters)

  1. Front Matter

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  2. Knowledge Discovery and Data Mining in Biomedical Informatics: The Future Is in Integrative, Interactive Machine Learning Solutions

    • Andreas Holzinger, Igor Jurisica
    Pages 1-18

  3. Visual Data Mining: Effective Exploration of the Biological Universe

    • David Otasek, Chiara Pastrello, Andreas Holzinger, Igor Jurisica
    Pages 19-33

  4. Darwin or Lamarck? Future Challenges in Evolutionary Algorithms for Knowledge Discovery and Data Mining

    • Katharina Holzinger, Vasile Palade, Raul Rabadan, Andreas Holzinger
    Pages 35-56

  5. On the Generation of Point Cloud Data Sets: Step One in the Knowledge Discovery Process

    • Andreas Holzinger, Bernd Malle, Marcus Bloice, Marco Wiltgen, Massimo Ferri, Ignazio Stanganelli et al.
    Pages 57-80

  6. Adapted Features and Instance Selection for Improving Co-training

    • Gilad Katz, Asaf Shabtai, Lior Rokach
    Pages 81-100

  7. Knowledge Discovery and Visualization of Clusters for Erythromycin Related Adverse Events in the FDA Drug Adverse Event Reporting System

    • Pinar Yildirim, Marcus Bloice, Andreas Holzinger
    Pages 101-116

  8. On Computationally-Enhanced Visual Analysis of Heterogeneous Data and Its Application in Biomedical Informatics

    • Cagatay Turkay, Fleur Jeanquartier, Andreas Holzinger, Helwig Hauser
    Pages 117-140

  9. A Policy-Based Cleansing and Integration Framework for Labour and Healthcare Data

    • Roberto Boselli, Mirko Cesarini, Fabio Mercorio, Mario Mezzanzanica
    Pages 141-168

  10. Interactive Data Exploration Using Pattern Mining

    • Matthijs van Leeuwen
    Pages 169-182

  11. Resources for Studying Statistical Analysis of Biomedical Data and R

    • Mei Kobayashi
    Pages 183-195

  12. A Kernel-Based Framework for Medical Big-Data Analytics

    • David Windridge, Miroslaw Bober
    Pages 197-208

  13. On Entropy-Based Data Mining

    • Andreas Holzinger, Matthias Hörtenhuber, Christopher Mayer, Martin Bachler, Siegfried Wassertheurer, Armando J. Pinho et al.
    Pages 209-226

  14. Sparse Inverse Covariance Estimation for Graph Representation of Feature Structure

    • Sangkyun Lee
    Pages 227-240

  15. Multi-touch Graph-Based Interaction for Knowledge Discovery on Mobile Devices: State-of-the-Art and Future Challenges

    • Andreas Holzinger, Bernhard Ofner, Matthias Dehmer
    Pages 241-254

  16. Intelligent Integrative Knowledge Bases: Bridging Genomics, Integrative Biology and Translational Medicine

    • Hoan Nguyen, Julie D. Thompson, Patrick Schutz, Olivier Poch
    Pages 255-270

  17. Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges

    • Andreas Holzinger, Johannes Schantl, Miriam Schroettner, Christin Seifert, Karin Verspoor
    Pages 271-300

  18. Protecting Anonymity in Data-Driven Biomedical Science

    • Peter Kieseberg, Heidelinde Hobel, Sebastian Schrittwieser, Edgar Weippl, Andreas Holzinger
    Pages 301-316

  19. Biobanks – A Source of Large Biological Data Sets: Open Problems and Future Challenges

    • Berthold Huppertz, Andreas Holzinger
    Pages 317-330

  20. On Topological Data Mining

    • Andreas Holzinger
    Pages 331-356
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Keywords

About this book

One of the grand challenges in our digital world are the large, complex and often weakly structured data sets, and massive amounts of unstructured information. This “big data” challenge is most evident in biomedical informatics: the trend towards precision medicine has resulted in an explosion in the amount of generated biomedical data sets. Despite the fact that human experts are very good at pattern recognition in dimensions of <= 3; most of the data is high-dimensional, which makes manual analysis often impossible and neither the medical doctor nor the biomedical researcher can memorize all these facts. A synergistic combination of methodologies and approaches of two fields offer ideal conditions towards unraveling these problems: Human–Computer Interaction (HCI) and Knowledge Discovery/Data Mining (KDD), with the goal of supporting human capabilities with machine learning.

This state-of-the-art survey is an output of the HCI-KDD expert network and features 19 carefully selected and reviewed papers related to seven hot and promising research areas: Area 1: Data Integration, Data Pre-processing and Data Mapping; Area 2: Data Mining Algorithms; Area 3: Graph-based Data Mining; Area 4: Entropy-Based Data Mining; Area 5: Topological Data Mining; Area 6 Data Visualization and Area 7: Privacy, Data Protection, Safety and Security.

Editors and Affiliations

  • Research Unit Human-Computer Interaction, Austrian IBM Watson Think Gruop, Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria

    Andreas Holzinger

  • IBM Life Sciences Discovery Centre, TECHNA for the Advancement of Technology for Health, Princess Margaret Cancer Centre, University Health Network, Toronto, Canada

    Igor Jurisica

Bibliographic Information

  • Book Title: Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

  • Book Subtitle: State-of-the-Art and Future Challenges

  • Editors: Andreas Holzinger, Igor Jurisica

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-662-43968-5

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2014

  • Softcover ISBN: 978-3-662-43967-8Published: 26 June 2014

  • eBook ISBN: 978-3-662-43968-5Published: 17 June 2014

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XX, 357

  • Number of Illustrations: 56 b/w illustrations

  • Topics: Data Mining and Knowledge Discovery, Information Storage and Retrieval, Health Informatics

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