Titlebook: Biological and Artificial Intelligence Environments; Bruno Apolloni,Maria Marinaro,Roberto Tagliaferri Conference proceedings 2005 Springe

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978-90-481-6863-7Springer Science+Business Media B.V. 2005

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https://doi.org/10.1007/978-3-642-95354-5al data sets, and the exploitation of large computing power. Moreover, often such tools and databases are developed by independent groups, so the task of enabling their composition and cooperation is even more difficult. Integrating Computational Grid and Web Services technologies can be a key solut

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Eine ausführliche Falldarstellungsk could be modified by genetic polymorphisms of enzymes involved in the metabolism of tobacco carcinogens and in the DNA repair mechanisms. To study this relationship, a data set comprising clinical (age, smoke, alcohol) and genetic data (the genetic polymorphism of 11 genes) was built; an XCS syst

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https://doi.org/10.1007/978-3-7091-6191-3Many supervised learning techniques, among them support vector machines, have been experimented, using also feature selection methods to reduce the dimensionality of the data. In alternative to feature selection methods, we proposed to apply random subspace ensembles, reducing the dimensionality of

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https://doi.org/10.1007/978-90-313-8396-2tivity ratio, and extracted from PA chest radiographs by a fully automatized method. The methods are a rule based system and a feed-forward neural network trained by back-propagation. Both the systems allow to recognize almost the 75% of false positives without losing any true positives.

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