Call for Papers for a Special Session

on

Application of Machine Learning in Constructing Biopatterns and Analyzing Bioprofiles

of

The Seventh International Conference on Machine Learning and Applications (ICMLA’08)

http://www.icmla-conference.org/icmla08/

December 11-13, 2008, San Diego , California   USA

 

 

 

Description and Scope

The evidence base for personalized medicine consists of an agglomeration of family history of disease, individual health history, host/risk factors, environmental and occupational exposures, electrophysiological parameters, tissue histopathology, genomic and proteomic patterns, and image-specific diagnostics extracted from the electronic medical record for optimizing treatment of diseases. Together, these sometimes disparate data sets form a biopattern, which is a personal “fingerprint” integrating multiple data sources for prediction of susceptibility to diseases and disease prognosis. The construction and analysis of biopatterns depends critically on machine learning to fuse data from demographic and health history, prognostics, histopathology, electronic medical records, large-scale high-throughput genomic and proteomic technology, signal, and image processing.

 

This session is an outgrowth of the EU Biopattern Consortium (www.biopattern.org) which currently is exploring how biopatterns can be exploited for individualized healthcare such as disease prevention, diagnosis and treatment.  Areas of focus include novel machine learning techniques for biopattern construction and analysis of an individual’s bioprofile, ranging from analysis of longitudinal data through data fusion from distributed secure databases, to exploratory bioinformatics.  

 

The concept of biopatterns focuses on tackling and reducing fragmentation in the new field of biopattern and bioprofile analysis to underpin e-health in the post-genome era. This session will bring together leading researchers in machine learning, bioinformatics and medical informatics from academia, the healthcare sector and industry in a new way, harnessing expertise and information to rapidly thrust forward the notion of biopatterns for expert systems and decision processing.  Ultimately, the goal of Biopattern is to provide a coherent and intelligent analysis of a citizen’s bioprofile in order to make analysis of their bioprofile remotely accessible to patients and clinicians; and to exploit bioprofile to combat major diseases such as cancer and complex traits.

 

The International Program Committee combines strengths in medical and bioinformatics as well as machine learning and biostatistics.

 

Topics

We encourage the submissions of papers on novel biopattern technologies including:

 

-Novel machine learning algorithms for biopatterns

-Biopattern and bioprofiling for individualized care

-Bioprofiling over Grid for eHealth

-Electrophysiological markers of disease/severity

-Disease/risk classification based on fused image and signal data

-Augmenting prognostic models of disease with genomic and proteomic data

-Improving diagnosis and care with biopatterns

-Fusion of classification and function approximation

-Decision support and expert systems for biopatterns

 

Audience

-Computer scientists

-Bioinformaticians

-Nueroinformaticions

-Medical informaticians

-Statisticians

-Molecular biologists

-Biomedical and electrical engineers

-Other researchers and developers

  

Important Dates

Submission deadline:                           June 15, 2008   July 15, 2008

Notification of acceptance:                  September 1, 2008

Camera ready final papers due:           October 1, 2008

Conference:                                         December 11-13, 2008

 

Submissions

Papers submitted for this workshop should be submitted by June 15, 2008   July 15, 2008, at the regular paper submission website (http://www.icmla-conference.org/icmla08). Papers should not exceed a maximum of 6 pages (including abstract, body, tables, figures, and references), and should be submitted as a pdf in 2-column IEEE format. LaTeX document class files for 2-column format can be found on the IEEE Author Tools web page here.

 

Proceedings

Accepted papers will be published in the IEEE conference proceedings, as a hardcopy. All accepted papers must be presented by one of the authors to be published in the conference proceedings.

 

Session Chairs

Leif Peterson, Center for Biostatistics, The Methodist Hospital Research Institute, Houston , Texas USA , E-mail: lepeterson <at> tmhs.org

Paulo Lisboa, School of Computing Sciences , Liverpool John Moores University , London , UK   E-mail: P.J.Lisboa <at> ljmu.ac.uk

 

Program Committee

Federico Ambrogi, Unit of Medical Statistics and Biometry, National Cancer Institute of Milan, Italy
Elia Biganzoli, Unit of Medical Statistics and Biometry, National Cancer Institute of Milan, Italy

Anne Denton, Dept. of Computer Science and Operations Research, North Dakota State University , USA

Terence Etchells, School of Computing and Mathematical Sciences, Liverpool John Moores University , UK

Alexandru Floares, SAIA - Solutions of Artificial Intelligence Applications, Romania

Emmanuel Ifeachor, School of Computing, Communications and Electronics. University of Plymouth , UK

Ioannis A. Kakadiaris, Dept. of Computer Science, University of Houston , USA

Mark A. Kon, Department of Mathematics and Statistics, Boston University, USA

José David Martín Guerrero, Dept. of Electrical Engineering, University of Valencia, Spain

Francesco Masulli, Dept. of Computer and Information Sciences, University of Genova, Italy

Lucila Ohno-Machado, Health Sciences and Technology(Medical School), Harvard University, Boston, USA

Roberto Tagliaferri, Dept. of Mathematics and Computer Science, University of Salerno , Italy

Azzam F.G. Taktak, Dept. of Clinical Engineering, Royal Liverpool University Hospital, UK

Thomas Villmann, Medical Department, University of Leipzig, Germany

Scott Smith, Dept. of Electrical and Computer Engineering, Boise State University, USA
Erzsebet Merenyi, Dept. of Electrical and Computer Engineering, Rice University, USA