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Descripción
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| Despite the huge findings made by the study of the behaviour of diseases, there are currently many non-cure or non-treatment diseases and only some of their symptoms can be beaten. Understanding how the diseases behave implies a complex analysis that together with the new technologies provide researchers with more calculation and observational capabilities, as well as novel approaches that allow us to observe how the diseases behave and relate in different environments with distinct factors. Current research aims to find new ways of characterizing the diseases based on phenotypic manifestations using knowledge extraction techniques from public sources. With the characterization of the diseases, a better understanding about the diseases and how similar they are can be achieved, leading for example to find new drugs that can be applied to different diseases. In order to carry out the present research we have made use of our own dataset of symptoms and diseases developed using an approach that allows us to generate phenotypic knowledge from the extraction of medical information from several data sources. | |
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Internacional
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Si |
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Nombre congreso
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2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS) |
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Tipo de participación
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960 |
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Lugar del congreso
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Revisores
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Si |
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ISBN o ISSN
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2372-9198 |
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DOI
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10.1109/CBMS.2019.00124 |
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Fecha inicio congreso
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Fecha fin congreso
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Desde la página
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596 |
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Hasta la página
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599 |
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Título de las actas
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