[CEUR Workshop Proceedings] Vol-765
urn:nbn:de:0074-765-1

Copyright © 2011 for the individual papers by the papers' authors. Copying permitted only for private and academic purposes. This volume is published and copyrighted by its editors.



LEMEDS'11
Learning from Medical Data Streams 2011


Proceedings of the Workshop on Learning from Medical Data Streams

In conjunction with the 13th Conference on Artificial Intelligence in Medicine (AIME'11)

Bled, Slovenia, July 6, 2011.


Edited by

Pedro Pereira Rodrigues *
Mykola Pechenizkiy **
Mohamed Medhat Gaber ***
João Gama ****

* University of Porto, LIAAD & CINTESIS & Faculty of Medicine, Alam. Prof. Hernani Monteiro, 4200-319 Porto, Portugal
** Eindhoven University of Technology, Department of Computer Science, P.O. Box 513, 5600 MB Eindhoven, the Netherlands
*** University of Portsmouth, School of Computing, Buckingham Building, BK1.41, Lion Terrace, Portsmouth, Hampshire, PO1 3HE, UK
**** University of Porto, LIAAD & Faculty of Economics, Rua de Ceuta, 118 - 6, 4050-190 Porto, Portugal




Table of Contents

    Introduction

  1. Learning from medical data streams: an introduction
    Pedro Pereira Rodrigues, Mykola Pechenizkiy, Mohamed Medhat Gaber, João Gama
  2. Disease monitoring and clinical decision support (invited talk abstract)
    Peter Lucas

    3. Session I

  3. Interpreting streaming biosignals: in search of best approaches to augmenting mobile health monitoring with machine learning for adaptive clinical decision support
    Val Jones, Ricardo Batista, Richard Bults, Harm Op Den Akker, Ing Widya, Hermie Hermens, Rianna Huis In'T Veld, Thijs Tonis, Miriam Vollenbroek-Hutten
  4. Improving clinical record visualization recommendations with Bayesian stream learning
    Pedro Pereira Rodrigues, Cláudia Dias, Ricardo Cruz-Correia

    5. Session II

  5. A process mining driven framework for clinical guideline improvement in critical care
    Carolyn McGregor, Christina Catley, Andrew James
  6. Contributions to an advisory system for changes detection in depth of anesthesia signals
    Raquel Sebastião, Margarida Silva, João Gama, Teresa Mendonça
  7. Improving cardiotocography monitoring: a memory-less stream learning approach
    Pedro Pereira Rodrigues, Raquel Sebastião, Cristina Costa Santos

    8. Panel Discussion

  8. Challenges and roadmap for machine learning from medical data streams (panel summary)
    Pedro Pereira Rodrigues
31-Oct-2011: submitted by Pedro Pereira Rodrigues
02-Nov-2011: published on CEUR-WS.org