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Descripción
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| The increasing availability of biological data is improving our understanding of diseases and providing new insight into their underlying relationships. Thanks to the improvements on both text mining techniques and computational capacity, the combination of biological data with semantic information obtained from medical publications has proven to be a very promising path. However, the limitations in the access to these data and their lack of structure pose challenges to this approach. In this document we propose the use of Wikipedia - the free online encyclopedia - as a source of accessible textual information for disease understanding research. To check its validity, we compare its performance in the determination of relationships between diseases with that of PubMed, one of the most consulted data sources of medical texts. The obtained results suggest that the information extracted from Wikipedia is as relevant as that obtained from PubMed abstracts (i.e. the free access portion of its articles), although further research is proposed to verify its reliability for medical studies. | |
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Internacional
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Si |
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Nombre congreso
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2018 IEEE 31st 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.2018.00076 |
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Fecha inicio congreso
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18/06/2018 |
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Fecha fin congreso
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21/06/2018 |
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Desde la página
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399 |
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Hasta la página
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404 |
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Título de las actas
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Proceedings of the International Symposium on Computer-Based Medical Systems |