The IDAMAP workshop series is devoted to computational methods
for data analysis in medicine, biology and pharmacology that present
results of analysis in the form communicable to domain experts and
that somehow exploit knowledge of the problem domain. Such knowledge
may be available at different stages of the data-analysis and
model-building process. Typical methods include data visualization,
data exploration, machine learning, and data mining.
Gathering in an informal setting, colloquium participants will have the
opportunity to meet and discuss selected technical topics in an
atmosphere which fosters the active exchange of ideas among researchers
and practitioners. The colloquium is intended to be a genuinely
interactive event and not a mini-conference, thus ample time will be
allotted for general discussion. A student challenge on data integration
will be organized. Author of the best solution will be invited to present
the work at the workshop.
A selection of revised and expanded IDAMAP 2009 papers will appear in
the Methods of Information in Medicine journal.
TOPICS
In the colloquium, the attention will be given to methodological issues of intelligent data analysis and on specific applications in medicine, biomedicine and pharmacology. In terms of methodology, topics include, but are not limited to:
data mining and machine learning techniques for supervised and unsupervised learning problems,
exploiting domain knowledge in learning and data analysis,
data visualization and exploration,
analysis of large data sets and relational data mining,
knowledge management and its integration with intelligent data analysis techniques, and
integration of intelligent data analysis techniques within biomedical information systems.
A paper submitted to the colloquium is expected to show a selected
methodology can help to solve relevant problems in medicine, and would
typically address the following issues:
What is the medical or clinical problem addressed?
Which knowledge representation was used?
Was any prior knowledge available? How was this used in the
data analysis or interpretation of results?
How is/can the newly discovered knowledge put into use?
Contributions that discuss particular applications of
intelligent data analysis techniques are invited, and can for example
cover analysis of medical and health-care data, data coming from
clinical bioinformatics data bases (like microarray data and DNA
sequence analysis), analysis of pharmacological data, drug design,
drug testing, and outcomes analysis.
PROBLEM OWNERS
In addition to regular scientific contributions, we welcome descriptions
of problems or data sets that could potentially benefit from an analysis
through Intelligent Data Analysis or Data Mining. Problem descriptions
must be submitted as abstracts and will be presented at the workshop.
They must briefly introduce the problem and provide an overview of
the main objectives of the analysis. After the presentations, ample
time will be reserved for discussion.
DATA ANALYSIS TOOLS
We also invite developers of data analysis tools to send an abstract with
the description of their tool, and give a demonstration during a special
demo session on data analysis tools at the colloquium. The abstract should
describe the underlying methodology of the tool and sketch the potential for
application in the field of intelligent data analysis in biomedicine. Preferably,
abstracts on data analysis tools should also briefly describe a case study
where the tool was used.
STUDENT CHALLENGE
The challenge will involve applying methods for intelligent and integrative
data analysis on multiple source of data. The task will be to build
a predictive model and use it to classify a set of test examples. A web
page will be available for data access and submission of predictions,
starting in May, 2009.
SCIENTIFIC PROGRAM
The scientific program of the colloquium will consist of
presentations on invitation,
presentation of accepted papers, and
demonstrations of data analysis tools.
We gather in an informal setting and there will be ample time for discussion.
SUBMISSION OF PAPERS
IDAMAP invites submissions of either short papers (2 pages, up to 1500
words, leading to a short presentation at the meeting) or full papers
(up to 6 pages/4500 words, leading to a long presentation at the
meeting). Data analysis tools and description of problems should be
submitted as abstracts (1 page, up to 750 words). Papers should be
written in English. Authors should send an electronic submission in PDF
format to both chairs ([email protected], [email protected]); please use "IDAMAP SUBMISSION YOUR_NAME" as a subject, where
YOUR_NAME is the surname of the first author. Alternatively to
preferred PDF, submissions using Post Script or MS Word format are
also welcome.
The submissions should be received no later than April 14, 2009. Manuscripts should be formatted two columns to a page, on A4 paper size, and with a 10-point times font for the text. A PDF-document is available with detailed instructions. We have prepared a set of LaTeX macros and a Microsoft Word template. All instructions and macros are the same as last year. Please submit your manuscript in PDF (preferred) or as MS Word file.
Submitted papers will be reviewed by at least two people of the program committee. Authors will be notified of acceptance/rejection by June 3, 2009. Accepted papers will appear in colloquium notes that will be distributed among registered participants.
JOURNAL PUBLICATION
A selection of contributors to IDAMAP 2009 will be invited to submit a revised
and expanded version of their paper for publication in Schattauer's Methods of
Information in Medicine journal. Publication is scheduled for late 2009/early 2010.
REGISTRATION
Details on payment and registration will be posted shortly on the AIME and
IDAMAP 2009 pages.