| Front matter
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pages |
Document retrieval and question answering in medical documents. A large-scale corpus challenge.
Curea Eric
[pdf] [bib]
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pp. 1–7 |
Adapting the TTL Romanian POS Tagger to the Biomedical Domain
Maria Mitrofan and Radu Ion
[pdf] [bib]
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pp. 8–14 |
Discourse-Wide Extraction of Assay Frames from the Biological Literature
Dayne Freitag, Paul Kalmar and Eric Yeh
[pdf] [bib]
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pp. 15–23 |
Classification based extraction of numeric values from clinical narratives
Maximilian Zubke
[pdf] [bib]
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pp. 24–31 |
Understanding of unknown medical words
Natalia Grabar and Thierry Hamon
[pdf] [bib]
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pp. 32–41 |
Entity-Centric Information Access with Human in the Loop for the Biomedical Domain
Seid Muhie Yimam, Steffen Remus, Alexander Panchenko, Andreas Holzinger and Chris Biemann
[pdf] [bib]
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pp. 42–48 |
One model per entity: using hundreds of machine learning models to recognize and normalize biomedical names in text
Victor Bellon and Raul Rodriguez-Esteban
[pdf] [bib]
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pp. 49–54 |
Towards Confidence Estimation for Typed Protein-Protein Relation Extraction
Camilo Thorne and Roman Klinger
[pdf] [bib]
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pp. 55–63 |
Identification of Risk Factors in Clinical Texts through Association Rules
Svetla Boytcheva, Ivelina Nikolova, Galia Angelova and Zhivko Angelov
[pdf] [bib]
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pp. 64–72 |
POMELO: Medline corpus with manually annotated food-drug interactions
Thierry Hamon, Vincent Tabanou, Fleur Mougin, Natalia Grabar and Frantz Thiessard
[pdf] [bib]
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pp. 73–80 |
Annotation of Clinical Narratives in Bulgarian language
Ivajlo Radev, Kiril Simov, Galia Angelova and Svetla Boytcheva
[pdf] [bib]
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pp. 81–87 |
Last modified on November 25, 2017, 1:45 a.m.