Smart Health

Open Problems and Future Challenges

  • Andreas Holzinger
  • Carsten Röcker
  • Martina Ziefle
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8700)

Table of contents

  1. Front Matter
    Pages I-XIV
  2. Andreas Holzinger, Carsten Röcker, Martina Ziefle
    Pages 1-20
  3. Michael Duerr-Specht, Randy Goebel, Andreas Holzinger
    Pages 21-39
  4. Björn Gottfried, Hamid Aghajan, Kevin Bing-Yung Wong, Juan Carlos Augusto, Hans Werner Guesgen, Thomas Kirste et al.
    Pages 41-69
  5. Melvin Isken, Thomas Frenken, Melina Frenken, Andreas Hein
    Pages 71-98
  6. Gabriele Bleser, Daniel Steffen, Attila Reiss, Markus Weber, Gustaf Hendeby, Laetitia Fradet
    Pages 99-124
  7. Gregor Rebel, Francisco Estevez, Peter Gloesekoetter, Jose M. Castillo-Secilla
    Pages 125-159
  8. Michel Vacher, Benjamin Lecouteux, François Portet
    Pages 161-188
  9. Norimichi Ukita, Daniel Kaulen, Carsten Röcker
    Pages 189-208
  10. Stefan Zwicklbauer, Christin Seifert, Michael Granitzer
    Pages 209-235
  11. Klaus Donsa, Stephan Spat, Peter Beck, Thomas R. Pieber, Andreas Holzinger
    Pages 237-260
  12. Heimo Müller, Robert Reihs, Kurt Zatloukal, Fleur Jeanquartier, Roxana Merino-Martinez, David van Enckevort et al.
    Pages 261-273
  13. Back Matter
    Pages 275-275

About this book

Introduction

Prolonged life expectancy along with the increasing complexity of medicine and health services raises health costs worldwide dramatically. Whilst the smart health concept has much potential to support the concept of the emerging P4-medicine (preventive, participatory, predictive, and personalized), such high-tech medicine produces large amounts of high-dimensional, weakly-structured data sets and massive amounts of unstructured information. All these technological approaches along with “big data” are turning the medical sciences into a data-intensive science. To keep pace with the growing amounts of complex data, smart hospital approaches are a commandment of the future, necessitating context aware computing along with advanced interaction paradigms in new physical-digital ecosystems.

The very successful synergistic combination of methodologies and approaches from Human-Computer Interaction (HCI) and Knowledge Discovery and Data Mining (KDD) offers ideal conditions for the vision to support human intelligence with machine learning.

The papers selected for this volume focus on hot topics in smart health; they discuss open problems and future challenges in order to provide a research agenda to stimulate further research and progress.

Keywords

HCI ambient assisted living big data computational intelligence context awareness data centric medicine decision support interactive data mining keyword detection knoweldge bases knoweldge discovery machine learning medical decision support medical informatics natural language processing pervasive health smart home ubiquitous computing visualization wearable sensors

Editors and affiliations

  • Andreas Holzinger
    • 1
  • Carsten Röcker
    • 2
  • Martina Ziefle
    • 3
  1. 1.Research Unit HCI-KDDMedical University of GrazGrazAustria
  2. 2.Industrial HCI Research LabFraunhofer InstituteLemgoGermany
  3. 3.Human-Computer Interaction CenterRWTH Aachen UniversityAachenGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-16226-3
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-16225-6
  • Online ISBN 978-3-319-16226-3
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book

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