Abstract
Automatic methods are being developed and applied to transform textual biomedical information into machine-readable formats. Machine learning techniques have been a prominent approach to this problem. However, there is still a lack of systems that are easily accessible to users. For this reason, we developed a web tool to facilitate the access to our text mining framework, IICE (Identifying Interactions between Chemical Entities). This tool annotates the input text with chemical entities and identifies the interactions described between these entities. Various options are available, which can be manipulated to control the algorithms employed by the framework and to the output formats.
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Lamurias, A., Clarke, L.A., Couto, F.M. (2015). IICE: Web Tool for Automatic Identification of Chemical Entities and Interactions. In: Bifet, A., et al. Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2015. Lecture Notes in Computer Science(), vol 9286. Springer, Cham. https://doi.org/10.1007/978-3-319-23461-8_31
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DOI: https://doi.org/10.1007/978-3-319-23461-8_31
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