[Announcements] ASOC journal (IF: 3.907): Special Issue on Bio-Inspired Optimization Techniques for BioMedical Data Analysis: Methods and Applications

Dear Colleague,

It is a pleasure for me to invite you to participate to the Virtual 
Special Issue on "Bio-Inspired Optimization Techniques for BioMedical 
Data Analysis: Methods and Applications", Applied Soft Computing 
journal, Elsevier (Impact Factor:3.907)


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Applied Soft Computing journal (Elsevier) - IF 2018: 3.907
Special Issue on Bio-Inspired Optimization Techniques for
BioMedical Data Analysis: Methods and Applications
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The intertwining disciplines of bio-inspired computing (BIC), biomedical 
imaging and data analysis are major fields of computer science, computer 
engineering and electrical and electronic engineering, which have 
attracted the interest of many researchers. The past and on-going 
research covers a wide range of topics and tasks, from fundamental 
research to a huge number of real-world industrial applications.

An exhaustive search is impractical in solving problems. Optimization 
provides a powerful tool for solving learning problems and data 
analysis. Designing and implementing optimization algorithms are based 
on several methods and have superior performance in many problems. 
However, in several applications, the search space increases 
exponentially with the problem size. In order to overcome the 
limitations and to solve efficiently larger scale of combinatorial and 
highly nonlinear optimization problems, sets of more flexible and 
adaptable algorithms are compulsory. BioMedical data analyses are 
driving new optimization research trends mainly based on machine 
learning and artificial intelligence, motivating intersections with 
biomedical imaging & data analysis and systems development. Bio-inspired 
computing is oriented toward applying outstanding information-processing 
aptitudes of the natural realm to the computation domain. It establishes 
a strong relationship with computational biology and other 
biology-inspired computing models due to its effectiveness and 
uniqueness even though it is still relatively new trend. Some 
meta-heuristic search algorithms with population-based framework are 
capable of handling optimization in high-dimensional real-world problems 
in several domains including engineering, medicine, industry, education, 
and military. The discipline of Bio-inspired optimization algorithms is 
a major field of computational intelligence, soft computing and 
optimization at large, which has attracted the interest of many 
researchers. These algorithms provide efficient tools to those problems, 
which cannot be solved using traditional and classical mathematical 
methods, as often the algorithms do not require any mathematical 
condition to be satisfied.

The overall aim of this special issue is to collect state-of-the-art 
contributions on the latest research and development, up-to-date issues, 
and challenges in the fields of Bio Inspired Computing and BioMedical 
Data Analysis, and related applications. Proposed submissions should be 
original, unpublished, and present novel in-depth fundamental research 
contributions either from a methodological perspective or from an 
application point of view.

The topics of interest are strictly limited to:

1. New theories and methods in different BIC paradigms applied to 
Biomedical data analysis, such as

- Ant Colony Systems
- Artificial Immune Systems
- Artificial Neural Networks
- Cellular Automata
- Cognitive Modelling
- DNA Computing
- Differential Evolution
- Emergent Systems
- Evolutionary Computations
- Evolutionary Strategies/Programming
- Genetic Algorithms/Programming
- Granular Computing
- Organic Computing
- Particle Swarm Optimization
- Swarm-based Algorithms

2. Applications of BIC and BIC-related techniques to biomedical data 
analysis, including

- Biomedical intelligent decision support system
- Computer aided diagnosis
- Parallel processing
- Biomedical applications
- Internet of Health Things
- Health 4.0
- Virtual environments and Bio-inspired robotics
- Automatic feature extraction and construction in complex images
- Medical and bio-medical data analysis
- eHealth, mHealth and Telemedicine

IMPORTANT: Please choose VSI: BioMedical Data Analysisî when specifying 
the Article Type.

Proposed Schedule:

- Virtual Special Issue start: July 1st, 2018
- First Round of Review: Maximum 3 months after submission date
- Virtual Special Issue closing date: November 30, 2018

FOR FURTHER INFORMATION:
https://www.journals.elsevier.com/applied-soft-computing/call-for-papers/special-issue-on-bio-inspired-optimization-techniques-for-bi 

Received on Thursday, 2 August 2018 14:41:46 UTC