VSI on Applied Soft Computing journal (Elsevier) - IF: 3.907 - Bio-Inspired Optimization Techniques for BioMedical Data Analysis: Methods and Applications

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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