Titlebook: Biomedical Applications Based on Natural and Artificial Computing; International Work-C José Manuel Ferrández Vicente,José Ramón Álvarez-S

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K. J. Hamelynck,J.-L. Briard,M. J. Pappascomes compared to a task-free interval during which users are instructed to relax. We report that cortical oscillations of . in delta and theta frequencies clearly synchronize at the onset and at the end of a . task, what might be a physiological marker for task switching that could be useful for im

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Non-stationary Turbulent Flows,s and afterwards we discuss the results obtained in the above-mentioned scenario. We would like to emphasize that for this scenario the human agents and the robot use limited linguistic words to facilitate coordination. These verbal exchanges are based on a common language (a lexicon plus grammar ru

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Biomedical Applications Based on Natural and Artificial ComputingInternational Work-C

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Koniocortex-Like Network Unsupervised Learning Surpasses Supervised Results on WBCD Breast Cancer Daential for complex tasks with unsupervised learning. Now for the first time, its competitive results are proved in a relevant standard real application that is the objective of state-of-the-art research: the diagnosis of breast cancer data from the Wisconsin Breast Cancer Database.

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Ongoing Work on Deep Learning for Lung Cancer Predictionlti-center CTA data. First we have normalized in intensity the images. Then we have devised an auto encoder architecture with convolutional layers to obtain a compressed representation of the lung images. These representations are fed as features to a random forest classifier.

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