Call for Papers INTELLIGENT DATA ANALYSIS IN MEDICINE AND PHARMACOLOGY Monday, September 6, 2004 A One-Day Workshop at Stanford University, Stanford, CA Organized in collaboration with Intelligent Data Analysis and Data Mining Workgroup of International Medical Informatics Association, and Knowledge Discovery & Data Mining SIG of American Medical Informatics Association http://idamap.org/idamap2004 Submission: June 25, 2004 Notification: July 15, 2004 Camera-ready: July 30, 2004 GENERAL INFORMATION IDAMAP-2004, a one day Workshop on intelligent data analysis in medicine and pharmacology, will be held at Stanford University, Paolo Alto, CA, on Monday, 6th of September, 2004, just prior to MEDINFO Conference. This is the ninth IDAMAP Workshop: the former ones were held in Budapest in 1996, Nagoya in 1997, Brighton in 1998, Washington DC in 1999, Berlin in 2000, London in 2001, Lyon in 2002, and Cyprus in 2003. 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 expert 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 mining, temporal abstraction, machine learning, and data visualization. Gathering in an informal setting, workshop 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 workshop is intended to be a genuinely interactive event and not a mini-conference, thus ample time will be allotted for general discussion. TOPIC In the workshop 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 techniques, including machine learning, clustering, neural networks, etc., - other techniques for construction of predictive models, - data visualization, - analysis of large data sets, - relational data mining, - interpretation of time-ordered data (derivation and revision of temporal trends and other forms of temporal data abstraction), - knowledge representation, - knowledge management and its integration with intelligent data analysis techniques, - utility of background knowledge in data analysis, - integration of intelligent data analysis techniques within biomedical information systems. A paper submitted to the workshop 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. We also invite papers on data analysis tools. Such papers can overview a particular tool and describe why and how this could be suitable for intelligent data analysis in medicine and other application areas that are a subject of the IDAMAP workshop. Preferably, the papers on data analysis tools would also describe a case study where the tool was used. SCIENTIFIC PROGRAM The scientific program of the workshop will consist of presentations of invited and accepted papers and panel discussion. Workshop will feature several invited talks, including the talks by - Michael Kattan, Memorial Sloan-Kettering Cancer Center, New York, NY, who will give a talk on cancer prediction models and their utility in clinical practice (see also pages on cancer nomograms at http://www.baylorcme.org/nomogram/modules.cfm), - Marco Ramoni, Harvard Medical School, Boston, MA, who will talk on Bayesian networks for integrative genomics. SUBMISSION & PUBLICATION OF ACCEPTED PAPERS IDAMAP invites submissions of either short papers (2 pages, up to 1500 words, leading to a poster/short presentation at the meeting) or full papers (up to 6 pages/4500 words, leading to a panel presentation at the meeting). Papers should be written in English. Authors should send an electronic submission in PDF format to both chairs (blaz.zupan@fri.uni-lj.si, jholmes@cceb.med.upenn.edu); 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 June 5, 2004. Additional formatting instructions and instructions for authors are available on Workshop's home page at http://idamap.org/idamap2004. Authors will be notified of acceptance by June 28, 2004. Papers will appear in workshop notes that will be distributed to registered participants. A subsequent publication of selected and revised papers in peer-reviewed journal is planned. REGISTRATION The registration fee for the IDAMAP workshop is 50 US dollars. Details on payment and registration process will be announced later this spring and will be posted on workshop's web page, http://idamap.org/idamap2004). ORGANIZING COMMITTEE - Mark Musen, Stanford University, Stanford, USA (local chair) - Samson Tu, Stanford University, Stanford, USA - Amar Das, Stanford University, Stanford, USA PROGRAM COMMITTEE (TENTATIVE) - Blaz Zupan, University of Ljubljana, Slovenia (chair) - John H. Holmes, University of Pennsylvania School of Medicine, USA (chair) - Lars Asker, Stockholm University, Sweden - Ameen Abu-Hanna, Academic Medical Center, Univ. of Amsterdam, The Netherlands - J. Robert Beck, Fox Chase Cancer Center, USA - Riccardo Bellazzi, University of Pavia, Italy - Janez Demsar, University of Ljubljana, Slovenia - Dragan Gamberger, Rudjer Boskovic Institute, Croatia - Werner Horn, Austrian Research Institute for AI, Austria - Elpida Keravnou-Papaeliou, University of Cyprus, Cyprus - Matjaz Kukar, University of Ljubljana, Slovenia - Nada Lavrac, J. Stefan Institute, Slovenia - Xiaohui Liu, Brunel University, UK - Peter Lucas, University of Aberdeen, UK - Silvia Miksch, Vienna University of Technology, Austria - Katharina Morik, University of Dortmund, Germany - Niels Peek, Academic Medical Center, Univ. of Amsterdam, The Netherlands - Lucila Ohno-Machado, Harvard Medical School and Massachusetts Institute of Technology, Boston, USA - Carlo Combi, University of Verona, Italy - Michel Dojat, Universite Joseph Fourier, Grenoble, France - Steve Rees, Aalborg University, Denmark - Paola Sebastiani, University of Massachusetts, Amherst, USA - Jim Hunter, University of Aberdeen, UK - Yuval Shahar, Ben-Gurion University of the Negev, Israel - Adam B. Wilcox, University of Utah, USA _______________________________________________________________________