Dear Colleague,<\/p>\n
It is a pleasure for me to invite you to participate to the Virtual
\nSpecial Issue on “Bio-Inspired Optimization Techniques for BioMedical
\nData Analysis: Methods and Applications”, Applied Soft Computing
\njournal, Elsevier (Impact Factor:3.907)<\/p>\n
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\nApplied Soft Computing journal (Elsevier) – IF 2018: 3.907
\nSpecial Issue on Bio-Inspired Optimization Techniques for
\nBioMedical Data Analysis: Methods and Applications
\n====================================<\/p>\n
The intertwining disciplines of bio-inspired computing (BIC), biomedical
\nimaging and data analysis are major fields of computer science, computer
\nengineering and electrical and electronic engineering, which have
\nattracted the interest of many researchers. The past and on-going
\nresearch covers a wide range of topics and tasks, from fundamental
\nresearch to a huge number of real-world industrial applications.<\/p>\n
An exhaustive search is impractical in solving problems. Optimization
\nprovides a powerful tool for solving learning problems and data
\nanalysis. Designing and implementing optimization algorithms are based
\non several methods and have superior performance in many problems.
\nHowever, in several applications, the search space increases
\nexponentially with the problem size. In order to overcome the
\nlimitations and to solve efficiently larger scale of combinatorial and
\nhighly nonlinear optimization problems, sets of more flexible and
\nadaptable algorithms are compulsory. BioMedical data analyses are
\ndriving new optimization research trends mainly based on machine
\nlearning and artificial intelligence, motivating intersections with
\nbiomedical imaging & data analysis and systems development. Bio-inspired
\ncomputing is oriented toward applying outstanding information-processing
\naptitudes of the natural realm to the computation domain. It establishes
\na strong relationship with computational biology and other
\nbiology-inspired computing models due to its effectiveness and
\nuniqueness even though it is still relatively new trend. Some
\nmeta-heuristic search algorithms with population-based framework are
\ncapable of handling optimization in high-dimensional real-world problems
\nin several domains including engineering, medicine, industry, education,
\nand military. The discipline of Bio-inspired optimization algorithms is
\na major field of computational intelligence, soft computing and
\noptimization at large, which has attracted the interest of many
\nresearchers. These algorithms provide efficient tools to those problems,
\nwhich cannot be solved using traditional and classical mathematical
\nmethods, as often the algorithms do not require any mathematical
\ncondition to be satisfied.<\/p>\n
The overall aim of this special issue is to collect state-of-the-art
\ncontributions on the latest research and development, up-to-date issues,
\nand challenges in the fields of Bio Inspired Computing and BioMedical
\nData Analysis, and related applications. Proposed submissions should be
\noriginal, unpublished, and present novel in-depth fundamental research
\ncontributions either from a methodological perspective or from an
\napplication point of view.<\/p>\n
The topics of interest are strictly limited to:<\/p>\n
1. New theories and methods in different BIC paradigms applied to
\nBiomedical data analysis, such as<\/p>\n
– Ant Colony Systems
\n– Artificial Immune Systems
\n– Artificial Neural Networks
\n– Cellular Automata
\n– Cognitive Modelling
\n– DNA Computing
\n– Differential Evolution
\n– Emergent Systems
\n– Evolutionary Computations
\n– Evolutionary Strategies\/Programming
\n– Genetic Algorithms\/Programming
\n– Granular Computing
\n– Organic Computing
\n– Particle Swarm Optimization
\n– Swarm-based Algorithms<\/p>\n
2. Applications of BIC and BIC-related techniques to biomedical data
\nanalysis, including<\/p>\n
– Biomedical intelligent decision support system
\n– Computer aided diagnosis
\n– Parallel processing
\n– Biomedical applications
\n– Internet of Health Things
\n– Health 4.0
\n– Virtual environments and Bio-inspired robotics
\n– Automatic feature extraction and construction in complex images
\n– Medical and bio-medical data analysis
\n– eHealth, mHealth and Telemedicine<\/p>\n
IMPORTANT: Please choose VSI: BioMedical Data Analysis\u00ee when specifying
\nthe Article Type.<\/p>\n
Proposed Schedule:<\/p>\n
– Virtual Special Issue start: July 1st, 2018
\n– First Round of Review: Maximum 3 months after submission date
\n– Virtual Special Issue closing date: November 30, 2018<\/p>\n