AIMDM'99 -- Call for Papers for the workshop
** Prognostic Models in Medicine **
Artificial Intelligence and Decision Analytic Approaches
during the
Joint European Conference on Artificial Intelligence
in Medicine and Medical Decision Making (AIMDM'99)
in Aalborg, Denmark, 20th - 24th June 1999
(WWW version of this CFP: http://www.cs.uu.nl/~lucas/ipm-aimdm99.html)
(WWW version of of AIMDM http://www.miba.auc.dk/AIMDM99/)
----------------------------------------------------------------------------
Important dates
* Submission deadline of structured abstracts: 1 March 1999
* Notification of acceptance: 15 April 1999
* Conference: 20th - 24th June 1999
* Workshop: Sunday, 20th June 1999
Prognostic models are increasingly used in medicine to predict the
natural course of disease, or the expected outcome after
treatment. Prognosis forms an integral part of systems for treatment
selection and treatment planning. In evaluating quality of care,
prognostic models are used for predicting outcome, such as mortality,
which is compared with the actual measured outcome. Furthermore,
prognostic models may play an important role in guiding diagnostic
problem solving, e.g. by only requesting information concerning tests,
of which the outcome affects knowledge of the prognosis.
In recent years several methods and techniques from the fields of
artificial intelligence, decision theory and statistics have been
introduced into models of the medical management of patients
(diagnosis, treatment, follow-up); in some of these models, assessment
of the expected prognosis constitutes an integral part. Typically,
recent prognostic methods rely on explicit (patho)physiological
models, which may be combined with traditional models of life
expectancy. Examples of such domain models are causal disease models,
and physiological models of regulatory mechanisms in the human body.
Such model-based approaches have the potential to facilitate the
development of actual systems, because the medical domain models can
be (partially) obtained from the medical literature.
Various methods have been suggested for the representations of such
domain models ranging from quantitative and probabilistic approaches
to symbolic and qualitative ones. Semantic concepts such as time,
e.g. for modelling the progressive changes of regulatory mechanisms,
have formed an important and challenging modelling issue. Moreover,
automatic learning techniques of such models have been proposed. When
model construction is hard, less explicit domain models have been
studied such as the use of case-based and neural network representations
and their combination with more explicit domain models. In medical decision
analysis, where the theories of probability and utility are combined,
various representations and techniques are suggested such as decision
trees, regression models, and representations in which advantage is taken
from the Markov assumption (such as in Markov decision problems).
This workshop aims at bringing together various theoretical and
practical approaches to computational prognosis that comprise the
state of the art in this field. This workshop is a follow up on the
initiative started with the successful invited session on "Intelligent
Prognostic Methods in Medical Diagnosis and Treatment Planning" in
1998 during the conference "Computational Engineering in Systems
Applications 1998 (cesa'98)
(http://www.cs.ruu.nl/~lucas/ipm-cesa98.html) which has resulted in a
special issue on prognosis of the journal Artificial Intelligence in
Medicine.
Papers are sought that describe medical prognosis applications using
methods and techniques from artificial intelligence, decision theory,
and statistics as well as papers proposing theoretical foundations of
such methods. The workshop will also include one or more invited talks
(details will appear in due time on the corresponding WWW-page of this
workshop and the AIMDM'99 pages).
Topics of interest
Papers are sought on topics including, but not limited to:
* Modelling and Reasoning:
o the specification of prognostic models, possibly as part of
diagnostic or therapy-planning applications
o representation and reasoning about (multiple) model types such as
empirical, anatomical and (patho)physiological ones
o representation of and reasoning with time
o qualitative representation and reasoning
o decision modelling and analysis
o (dynamic) probabilistic networks
o representation and interpretations of strategies and guidelines
o health care quality assurance
o technology assessment and health policy making
o function-based representation and reasoning
o case-based representation and reasoning
* Knowledge Acquisition:
o acquisition of the medical prognostic models
o automated learning of domain or task models using machine learning
and data-mining techniques
* Formalisation:
o use of logical, set-theoretical or probabilistic methods to
formalise various aspects of prognosis and therapy planning
* Medical Applications:
o clinical context of actual prognostic models
o role of prognostic models in diagnosis or treatment planning of a
specific disease
o evaluation of prognostic models
Each submission will be refereed by at least two members of the
programme committee. Accepted papers will appear in the working notes
of the workshop "Prognostic Models in Medicine: Artificial
Intelligence and Decision Analytic Approaches". Attempts are made to
organise a special issue of a suitable international journal based on
the best papers.
Instructions to authors
Structured abstracts (up to 4 pages) are to be addressed to the first
co-chair and should be written in English with a short abstract and a
list of keywords. Electronic submissions by e-mail are encouraged
(either postscript files or plain text). Alternatively, 3 paper copies
may be submitted. The accepted abstracts will appear in the working
notes. Note that authors planning to submit a structured abstract to
the workshop may also submit their contributions (full paper or
structured abstract) to the main conference of AIMDM'99.
Registration fee
Workshop only 750 DKK, for participants of AIMDM'99 500 DKK. The fee
includes light refreshments and lunch.
Workshop organization
Co-Chairs:
Ameen Abu-Hanna, University of Amsterdam, The Netherlands
Peter Lucas, Utrecht University, The Netherlands
Programme committee
A. Abu-Hanna, The Netherlands
S. Andreassen, Denmark
P.M.M. Bossuyt, The Netherlands
J. Fox, UK
L.C. van der Gaag, The Netherlands
J.D.F. Habbema, The Netherlands
P. Haddawy, USA
P. Hammond, UK
E. Keravnou, Cyprus
N. Lavrac, Slovenia
J. van der Lei, The Netherlands
P.J.F. Lucas, The Netherlands
L. Ohno-Machado, USA
M. Ramoni, UK
M. Stefanelli, Italy
Th. Wetter, Germany
J. Wyatt, UK
For more information about the workshop please contact one of the
co-chairs.
----------------------------------------------------------------------------
Ameen Abu-Hanna Peter Lucas
Dept. of Medical Informatics Dept. of Computer Science
Academic Medical Center Utrecht University
University of Amsterdam Padualaan 14
Meibergdreef 15 3584 CH Utrecht
1105 AZ Amsterdam The Netherlands
The Netherlands
Telephone: +31 20 565959 Telephone: +31 30 2534094
Fax : +31 20 6919840 Fax: +31 30 2513791
A.Abu-Hanna@amc.uva.nl lucas@cs.uu.nl