Special Session on
Machine Learning for Biomedical Literature Analysis and Text Retrieval
in the International Conference for Machine Learning and Applications 2011
http://www.icmla-conference.org/icmla11/

December 18-21, 2011   Honolulu, Hawaii, USA

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AIMS AND SCOPE

The purpose of this session is to present novel research of machine learning techniques for natural language processing particularly in the biomedical domain. The amount of biomedical literature has grown exponentially within the last decade. The resulting abundance of scholarly material is of significant importance to researchers and healthcare professionals. However it is only valuable if efficient and reliable ways of accessing and analyzing that information are available.

Advances in machine learning techniques can improve the retrieval and analysis of biomedical information. We invite researchers to submit papers with their recent research on machine learning methods applied specifically to the analysis and processing of unstructured biomedical text, clinical text and any other healthcare related text media. We strongly encourage authors to submit papers describing their algorithmic contributions, methodological contributions, and computational results concerning biomedical text analysis as their main application. Papers are sought on a range of topics in this area that include, but are not limited to:

• Natural Language Processing
• Information Retrieval
• Image Data Retrieval
• Concept Identification / Named Entity Recognition
• Event Recognition
• Relationship Identification
• Semantics and Understanding
• Knowledge Discovery
• Inference
• Summarization
• Parsing

And more general topics such as:

• Methods for Feature Generation

· Classification Techniques for Partially Annotated Data

• New Supervised, Semi-Supervised and Unsupervised Learning Methods
• New Applications of Existing Machine Learning Methods to Solve Important Practical Problems in this Area

Selected contributions from last year’s session were published in a special issue in BMC Bioinformatics. Again, for ICMLA’11, a selected group of papers will be considered for a special issue in BMC Bioinformatics and/or Database (Oxford Journals). We particularly invite all interested attendees to join our discussions during the presentations for the various aspects of learning, mining and turning unstructured biomedical text into intelligent information.

IMPORTANT DATES

Paper Submission Deadline	: July 15, 2011
Notification of acceptance	: September 2, 2011
Camera-ready papers & Pre-registration	: October 1, 2011
The ICMLA Conference	: December 18-21, 2011

The special session will be held as a part of the ICMLA 2011 conference. Authors should submit papers through the main conference submission website. Papers must correspond to the requirements detailed in the instructions to authors. Accepted papers must be presented by one of the authors to be published in the conference proceeding. All paper submissions will be handled electronically. Detailed instructions for submitting the papers are provided on the conference home page at http://www.icmla-conference.org/icmla11/

If you have any questions, do not hesitate to direct your questions to
Rezarta.Islamaj@nih.gov  or Lana.Yeganova@nih.gov

Special Session Organizers:

Rezarta Islamaj Dogan and Lana Yeganova
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health (NIH), USA

Program Committee Members:

• Alan Aronson, National Library of Medicine, USA
• Periklis Andritsos, Ontario Cancer Institute, University of Toronto, CA
• Olivier Bodenreider, National Library of Medicine, USA
• Kevin Cohen, The MITRE Corporation, USA
• Donald Comeau, National Center for Biotechnology Information, NIH, USA
• Mark Dredze, Johns Hopkins University, USA
• Vahan Grigoryan, Booz Allen Hamilton, USA
• Lynette Hirschman, The MITRE Corporation, USA
• Jin-Dong Kim, Database Center for Life Science, ROIS, Japan
• Sun Kim, National Center for Biotechnology Information, NIH, USA
• Hongfang Liu, Department of Health Sciences Research, Mayo Clinic, USA
• Zhiyong Lu, National Center for Biotechnology Information, NIH, USA
• Andrey Rzhetsky, University of Chicago, USA
• Hagit Shatkay, University of Delaware, USA
• Ian Soboroff, NIST, USA
• Manabu Torii, Georgetown University Medical Center, USA
• Lyle Ungar, University of Pennsylvania, USA
• Karin Verspoor, University of Colorado, USA
• W. John Wilbur, National Center for Biotechnology Information, NIH, USA