Titlebook: Biomedical Engineering Systems and Technologies; 10th International J Nathalia Peixoto,Margarida Silveira,Egon L. van de Conference proceed

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Mesure de la pression intracranienne use a 3D Convolutional Neural Network, which incorporates anatomical atlas information and bilateral comparison, to detect dense vessels. We use 112 non-contrast computed tomography (NCCT) scans for training of the detector and 58 scans for evaluation of its performance. We compare automatic dense

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https://doi.org/10.1007/978-88-470-1714-6etworks is 2EXPTIME-complete in the sizes of the network specifications. Due to this high complexity of the problem, only small networks consisting of a few genes were successfully analysed. Since the analysis of homeostasis of gene networks is based on the technique of . checking of Linear Temporal

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Giuseppe Fabrizi,Calogero Pagliarelloances. Many tools have been developed recently, however they are not always adequate for the increasing database volume. In this paper we propose an efficient method, called SKraken, that combines taxonomic tree and .-mers frequency counting. SKraken extracts the most representative .-mers for each

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Il TTO dell’Università di Perugiarom the genetic sequences, gene-expression data, network topology, homology, and domain information. Except for the sequence-based features, the others require additional experimental data which is unavailable for under-studied and newly sequenced organisms. Hence, here, we propose a sequence-based

Constrain

Il TTO dell’Università di Ferraraecies like virus, and phylogenies of non-biological objects like documents, images and database records. In character-based live phylogeny, the input is a matrix with . objects and . characters, such each position .,?. keeps the state of character . for the object .. The output is a tree where the i

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