Chemlistem: chemical named entity recognition using recurrent neural networks

Author:

Corbett PeterORCID,Boyle John

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Computer Graphics and Computer-Aided Design,Physical and Theoretical Chemistry,Computer Science Applications

Reference25 articles.

1. Krallinger M, Pérez-Pérez M, Pérez-Rodríguez G, Blanco-Míguez A, Fdez-Riverola F, Capella-Gutierrez S, Lourenço A, Valencia A (2017) The BioCreative V.5 evaluation workshop: tasks, organization, sessions and topics. In: Proceedings of the BioCreative V.5 challenge evaluation workshop, Barcelona, 2017, pp 8–10

2. Pérez-Pérez M, Rabal O, Pérez-Rodríguez G, Vazquez M, Fdez-Riverola F, Oyarzabal J, Valencia A, Lourenço A, Krallinger M (2017) Evaluation of chemical and gene/protein entity recognition systems at BioCreative V.5: the CEMP and GPRO patents tracks. In: Proceedings of the BioCreative V.5 challenge evaluation workshop, Barcelona, 2017, pp 11–18

3. Rabal O, Pérez-Pérez M, Pérez-Rodríguez G, Vazquez M, Fdez-Riverola F, Oyarzabal J, Valencia A, Lourenço A, Krallinger M (2018) Comparative assessment of named entity recognition strategies on medicinal chemistry patents for systems pharmacology. J Cheminform (in press)

4. Krallinger M, Rabal O, Lourenco A, Perez-Perez M, Perez-Rodriguez G, Vazquez M, Leitner F, Oyarzabal J, Valencia A (2015) Overview of the CHEMDNER patents task. In: Proceedings of the fifth BioCreative challenge evaluation workshop, 2015, pp 63–75

5. Leaman R, Wei C-H, Lu Z (2015) tmChem: a high performance approach for chemical named entity recognition and normalization. J Cheminform 7(Suppl 1):S3

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