[CFP] Applied Soft Computing journal - VSI on Bio-Inspired Optimization Techniques for BioMedical Data Analysis: Methods and Applications

*Apologies
          if you receive multiple copies of this CFP *

          

          Dear Sir or Madam,

          As guest editor, I
            kindly invite you to submit a paper to the VSI on
          Bio-Inspired Optimization Techniques for BioMedical Data
          Analysis: Methods and Applications. 

          

          

          ====================================
        Applied
          Soft Computing journal (Elsevier) - IF 2018: 3.907
        Special
          Issue on Bio-Inspired Optimization Techniques for 
        BioMedical
          Data Analysis: Methods and Applications
        ====================================
        
        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