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CALL FOR PAPERS

Special Issue
Advances in Medical Intelligent Decision Support Systems
Intelligent Decision Technologies (IDT) journal seeks original manuscripts for a Special Issue on Advances in Medical Decision Support Systems scheduled to appear in Vol. 3, No. 2, 2009.

The last few decades have witnessed significant advancements in intelligent computation techniques. Driven by the need to solve complex real-world problems, powerful and sophisticated intelligent data analysis technologies have been exploited or emerged, such as neural networks, support vector machines, evolutionary algorithms, clustering methods, fuzzy logic, particle swarm optimization, data mining, etc. In recent years, the volume of biological data has been increasing exponentially, thus, allowing significant learning and experimentation to be carried out using a multidisciplinary approach, which gives rise to many challenging problems. The foundation for any medical decision support is the medical knowledge base which contains the necessary rules and facts. This knowledge needs to be acquired from information and data in the fields of interest, such as medicine. Clinical decision-making is a challenging, multifaceted process. Its goals are precision in diagnosis and ins
titution of efficacious treatment. Achieving these objectives involves access to pertinent data and application of previous knowledge to the analysis of new data in order to recognise patterns and relations. As the volume and complexity of data have increased, use of digital computers to support data analysis has become a necessity. In addition to computerisation of standard statistical analysis, several other techniques for computer-aided data classification and reduction generally referred to as intelligent systems, have evolved. This special issue will focus on illustrative and detailed information about medical intelligent decision support systems and feature extraction/selection for automated diagnostic systems.

The focus of this special issue is on advances in medical intelligent decision support systems including determination of optimum classification schemes for the problem under study and also to infer clues about the extracted features. Topics include, but are not limited to, the following:

• Bioinformatics and Computational Biology
• Neural Networks, Fuzzy Logic Systems and Support Vector Machines in Biological Signal Processing
• Decision Support Systems and Computer Aided Diagnosis
• Biomedical Signal Processing
• Biomedical Imaging and Image Processing
• Modelling, Simulation, Systems, and Control

Paper submission: Submitted articles must not have been previously published or currently submitted for journal publication elsewhere. As an author, you are responsible for understanding and adhering to our submission guidelines. You can access them from http://www.iospress.nl. Please thoroughly read these before submitting your manuscript. Each paper will go through a rigorous review process.

Please note the following important dates:
Paper submission for review: November 30, 2008 (Final deadline)
Review results: January 15, 2009
Revised Paper submission: February 20, 2009
Final acceptance: March 1, 2009
Manuscript delivery to the publisher: April 15, 2009
Interested authors should submit digital copies (PDF preferred) of their papers (suggested paper length: 15 pages), including all tables, diagrams, and illustrations, to the Guest Editor, Dr. Vassilis S. Kodogiannis, by e-mail.

Guest Editorial Board

Guest Editor

Dr. Vassilis S. Kodogiannis
Centre for Systems Analysis, School of Computer Science,
University of Westminster, London HA1 3TP, United Kingdom
Tel: +44-20-79115000 ext.4250
Email: kodogiv@wmin.ac.uk

Co-Guest Editors

Dr. Ilias Petrounias
Manchester Business School (East)
The University of Manchester
Booth Street West
Manchester M15 6PB, United Kingdom
Tel: +44-161-3063386
Email: ilias.petrounias@manchester.ac.uk

Assoc. Prof. John N. Lygouras
Dept. of Electrical and Computer Engineering,
Democritus University of Thrace,
GR-67100, Xanthi, Greece
Tel.: +30-25410-79578
Email: ilygour@ee.duth.gr

About the Journal
Intelligent Decision Technologies (IDT): An International Journal is dedicated to advancing knowledge in the theory and application of intelligent technologies and systems that support decision making. We welcome a wide range of research papers including theoretical, analytical and empirical studies.
The field of intelligent decision making is expanding rapidly due, in part, to advances in Artificial Intelligence and Network-centric environments that can deliver the technology. Networks and the Internet have integrated to enable communication and coordination between dispersed systems. At the same time, AI techniques have demonstrated that they have matured sufficiently for practical applications. Since many applications involve some type of decision, IDT provides a forum for original research that has the potential to improve decision making using intelligent technologies. The field of intelligent decision technologies is interdisciplinary in nature, bridging computer science with its development of artificial intelligence, information systems with its development of decision support systems, and engineering with its development of systems. IDT seeks to attract research that is focused on applied technology while exploring its development at a fu
ndamental level.

Topics
IDT conference seeks an interchange of research on intelligent systems and intelligent technologies which enhance or improve decision making in industry, government and academia. The focus is interdisciplinary in nature, and includes research on all aspects of intelligent decision technologies, from fundamental development to the applied system. Papers concerned with theory, design, development, implementation, testing and evaluation of intelligent decision systems are welcomed. Topics include, but are not limited to: intelligent agents, fuzzy logic, multi-agent systems, artificial neural networks, genetic algorithms, expert systems, intelligent decision making support systems, information retrieval systems, geographic information systems, knowledge management systems that have the potential to support decision making in the areas of management, international business, finance, accounting, marketing, healthcare, military applications, production, networks,
traffic management, crisis response, human interfaces.