1,373,215 research outputs found

    Toward A Universal Biomedical Data Translator.

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    Development of method of matched morphological filtering of biomedical signals and images

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    Formalized approach to the analysis of biomedical signals and images with locally concentrated features is developed on the basis of matched morphological filtering taking into account the useful signal models that allowed generalizing the existing methods of digital processing and analysis of biomedical signals and images with locally concentrated features. The proposed matched morphological filter has been adapted to solve such problems as localization of the searched structural elements on biomedical signals with locally concentrated features, estimation of the irregular background aimed at the visualization quality improving of biological objects on X-ray biomedical images, pathologic structures selection on mammogram. The efficiency of the proposed methods of matched morphological filtration of biomedical signals and images with locally concentrated features is proved by experiments

    Using Neural Networks for Relation Extraction from Biomedical Literature

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    Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedical literature. Several relation extraction approaches have been proposed to identify relations between concepts in biomedical literature, namely, using neural networks algorithms. The use of multichannel architectures composed of multiple data representations, as in deep neural networks, is leading to state-of-the-art results. The right combination of data representations can eventually lead us to even higher evaluation scores in relation extraction tasks. Thus, biomedical ontologies play a fundamental role by providing semantic and ancestry information about an entity. The incorporation of biomedical ontologies has already been proved to enhance previous state-of-the-art results.Comment: Artificial Neural Networks book (Springer) - Chapter 1

    UK science press officers, professional vision and the generation of expectations

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    Science press officers can play an integral role in helping promote expectations and hype about biomedical research. Using this as a starting point, this article draws on interviews with 10 UK-based science press officers, which explored how they view their role as science reporters and as generators of expectations. Using Goodwin’s notion of ‘professional vision’, we argue that science press officers have a specific professional vision that shapes how they produce biomedical press releases, engage in promotion of biomedical research and make sense of hype. We discuss how these insights can contribute to the sociology of expectations, as well as inform responsible science communication.This project was funded by the Wellcome Trust (Wellcome Trust Biomedical Strategic Award 086034)

    On the proper treatment of pathologies in biomedical ontologies

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    In previous work on biomedical ontologies we showed how the provision of formal definitions for relations such as is_a and part_of can support new types of auto-mated reasoning about biomedical phenomena. We here extend this approach to the transformation_of characteristic of pathologies
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