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Description and Scope

Medicine and its scientific and technological background are rapidly and profoundly changing in the Information Age. The impact on the biomedical equipment used to produce and collect laboratory data, signals and images is impressive. New high throughput technologies have appeared and existing technologies have been radically transformed. For example, techniques like electroencephalography or radiography, which two decades ago seemed to reach a bottleneck, came to a new life and their importance as diagnostic tools is continuously increasing. As a result, our capacity to produce and record huge amount of complex biomedical data - patient conditions, diagnostic tests, treatments, outcomes, different kind of "omics" data (genomics/proteomics, etc), biosignals and images – have dramatically increased. This data provides an unprecedented source of information that can lead to potential improvements in medical diagnostic, prognostic, and individualized, optimized treatment strategy.

However, much more work is required. Although technology has brought about tremendous new sources of important biomedical data, we have not moved very far with regard to extracting the knowledge that lies latent in this data. In recent years, modern computer science has brought forth tremendous new tools such as artificial neural networks, fuzzy logic, evolutionary computing, support vector machines, and the like. Yet the professional, political and social issues that separate the medical community and the intelligent computing community have delayed the serious application of these tools to accelerate progress in translational medicine; genome to phenome, bench to bedside and clinical trials to public health.


We encourage papers describing new or applying existing intelligent computing methods to real and practical medical and health-care problems in which the biomedical problems are central. The topics of interest include, but are not limited to:

·         disease modeling, diagnosis and prevention 

·         prognostic and treatment outcome predictions

·         patient monitoring and alarm systems

·         optimization of patient-management workflows

·         biomedical data\text\web mining and data visualization

·         integration of biomedical data sources and domain knowledge

·         translational bioinformatics (genomics, proteomics, etc.)

·         biomedical signals and images processing

·         design of clinical trials

Submissions addressing theoretical problems should clearly outline the expected impact of the proposed solution to the medical field.


Medical Informaticians



Computer Scientists


Molecular Biologist and Medical Doctors

Biomedical Engineers

Session Chairs

Alexandru Floares, SAIA - Solutions of Artificial Intelligence Applications & Artificial Intelligence Department, Cancer Institute Cluj-Napoca, Romania Email: alexandru.floares<at>ieee.org

Florin Manolache, Scientific Computing, Carnegie Mellon University, Pittsburgh, USA, Email: florin<at>andrew.cmu.edu

Aaron Baughman, IBM Bethesda, MD, USA, Email: baaron<at>us.ibm.com

Program Committee

Christian Eggenberger, IBM Switzerland

Adam Gaweda, University of Louisville, USA

Barry Graham, IBM USA

Mweene Monze, IBM South Africa

Leif Peterson, Center for Biostatistics, TMHRI, USA

John J. Rice, IBM Research

Important Dates

Paper submission 

15 June

Notification of acceptance

25 June

Final papers

15 July


15-17 October


Papers must be prepared following the guidelines illustrated on the CIBB web site and should be not longer than 10 pages. 
The submission of papers will be done by sending the PDF to alexandru.floares<at>ieee.org
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