Please have a look at http://wcci2016.org/spsessions.php 

From Big Data to Big Knowledge Using Computational Intelligence in Biomedicine

Organized by Francesco Masulli, Sanaz Mostaghim and Alexandru G Floares 

Due to the explosive evolution of Information Technology and Computer Science, Biomedicine entered in Big Data Age, and this is really a scientific revolution, not just a fashion. As always, the technological aspects evolve faster than the scientific community mentality. Transforming Big Data into Big Knowledge and developing a Knowledge-Based Medicine require new visions and approaches. Companies, facing the Big Data challenges, are moving faster in the right direction than the biomedical community, being under a stronger competitive pressure. They were forced to renounce to wishful thinking, like the idea that a few variables, embedded in a few rules, discovered using the old fashion statistics, will give intelligent support for business decisions. We have to do the same for developing adequate diagnosis, prognosis, and response to treatment predictive models/tests.

On the positive side, the biomedical community has to realize that we are already in the Big Knowledge Age too. Curated facts from literature, either manually or by Text/Web Mining, are stored in large repositories and integrated as structured knowledge. Dedicated software tools (e.g., DAVID, Metacore, and Ingenuity Pathways Analysis) allow the users to search for knowledge, which could be represented in biologically meaningful ways, like pathways or networks.

Computational Intelligence (CI) methodologies, tailored to Big Data, and combined with a proper vision of living systems, e.g., as complex dynamical systems or networks of interacting entities, could pave the way to Knowledge-Based Medicine. Precision Medicine should be viewed not only as an increase in measurement's accuracy but also as highly accurate predictive models (Predictive Medicine), discovered from Big Data with CI tools. All the steps of the workflows from Big Data to Big Knowledge could greatly benefit from using all CI methodologies, and this is why this special session is addressed to all of the three sections of the WCCI 2016.

Scope and Topics

All the steps of the workflows from Big Data to Big Knowledge could greatly benefit from using all CI methodologies, and this is why this special session is addressed to all of the three sections of the WCCI 2016. Authors are encouraged to apply CI methods and emphasize how their results could be incorporated into the biomedical domain knowledge. Topics include, but are not limited to:

• Novel CI approaches for data analysis in biomedicine
• Scalable computational intelligence tools for biomedicine
• Deep Learning architecture, representations, unsupervised and supervised algorithms
• Hardware and Software solutions for Big Data Searching, Storing and Management
• Microarray and Next-Generation Sequencing Data Preprocessing and Analysis
• Biomedical imaging preprocessing and Analysis
• Integration of Microarray NGS OMICS and Clinical Data
• Structured and Unstructured Data/Text/Web Mining
• Natural Language Processing in Biomedicine
• Functional Analysis of differentially expressed and predictive genes
• Diagnosis, prognosis, and response to treatment predictive models
• Data Visualization and Visual Analytics
• Biomedical analysis pipelines, frameworks, and workflows.
• Pathways and network analysis and visualization
• Computational drug design and repositioning
• Clinical Decision Support Systems and Electronic Health Records