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The Summer School lasts for five days: it will start on Monday, September 20th at 10:00 and will last till Friday, September 24th at 13:00. A two-day workshop with the same topic on September 21st and 22nd forms part of the Summer School.

Overall, the topics discussed will include advances in:

  • computational intelligence methods (i.e. neural networks, fuzzy systems, evolutionary computation, swarm optimization, etc.)
  • advanced statistical methods for healthcare
  • computational intelligence contributions to the healthcare domain (e.g. clinical decision support, biomedicine, medical process mining, telemedicine, care management, optimization of operational processes, healthcare logistics)

An overview of the talks is given below.

The location for each day is the K10 room in the Paviljoen building at the TU/e (a map of the campus is available here (pdf) and a map of the Paviljoen building is available here).
The program is as follows (also available as a pdf file):

date:20 Sep.21 Sep.22 Sep.23 Sep.24 Sep.
09:00-09:30J. BezdekJ. ZuradaW.M.P. van der Aalst
Opening CIHC Workshop
10:00-10:30H. La PoutréJ.M. Keller

11:00-11:30J. BezdekBreakBreak
11:30-12:00T. WeijtersJ. Ramon
13:00-13:30T. Tervonen

13:30-14:00P. Lucas

M. VerleysenT. Weijters
15:00-15:30BreakR. Mans

15:30-16:00J. Sousa

16:00-16:30O. AmftJ. Garibaldi

19:00-CIHC Summer School Diner

The CIHC Summer School Diner takes place on Wednesday evening (September 22nd, 2010) at 19:00 in the University Club in the main building of the TU/e (see campus map).

W.M.P. van der AalstProcess Mining
O. AmftActivity and context recognition: challenges towards truly smart health assistant systems
J. Bezdekc-Means Clustering, with applications to image processing, very large data, and medical computing
J. GaribaldiNon-Stationary Fuzzy Sets in Medical Decision Making
J.M. KellerRecognition Technology in Eldercare
H. La PoutréAdaptive Logistics in Hospitals: Computational Intelligence Techniques and Agent-based Simulations
P. LucasThe Model-based Approach to Medical Decision Support
R. MansProcess Mining in Healthcare
J. RamonLearning predictive models from patient records, with application to intensive care
J.M.C. SousaFeature Selection using Ant Colony Optimization: Applications in Health Care
T. TervonenComputational methods for evidence-based decision support in pharmaceutical decision making
M. VerleysenMachine learning for high-dimensional data
A.J.M.M. WeijtersFlexible Heuristics Miner (FHM)
J. ZuradaTowards Better Understanding of Protein Secondary Structure: Extracting Prediction Rules
J. ZuradaBuilding Virtual Organizations and Computational Intelligence - Machine Learning Networks