Abstract is missing.
- Syntactic complexity measures for detecting Mild Cognitive ImpairmentBrian Roark, Margaret Mitchell, Kristy Hollingshead. 1-8 [doi]
- Determining the Syntactic Structure of Medical Terms in Clinical NotesBridget T. McInnes, Ted Pedersen, Serguei Pakhomov. 9-16 [doi]
- The Role of Roles in Classifying Annotated Biomedical TextSon Doan, Ai Kawazoe, Nigel Collier. 17-24 [doi]
- On the unification of syntactic annotations under the Stanford dependency scheme: A case study on BioInfer and GENIASampo Pyysalo, Filip Ginter, Veronika Laippala, Katri Haverinen, Juho Heimonen, Tapio Salakoski. 25-32 [doi]
- An Unsupervised Method for Extracting Domain-specific Affixes in Biological LiteratureHaibin Liu, Christian Blouin, Vlado Keselj. 33-40 [doi]
- Combining multiple evidence for gene symbol disambiguationHua Xu, Jung-Wei Fan, Carol Friedman. 41-48 [doi]
- Mining a Lexicon of Technical Terms and Lay EquivalentsNoemie Elhadad, Komal Sutaria. 49-56 [doi]
- Annotation of Chemical Named EntitiesPeter T. Corbett, Colin R. Batchelor, Simone Teufel. 57-64 [doi]
- Recognising Nested Named Entities in Biomedical TextBeatrice Alex, Barry Haddow, Claire Grover. 65-72 [doi]
- Exploring the Efficacy of Caption Search for Bioscience Journal Search InterfacesMarti A. Hearst, Anna Divoli, Jerry Ye, Michael A. Wooldridge. 73-80 [doi]
- ConText: An Algorithm for Identifying Contextual Features from Clinical TextWendy W. Chapman, John N. Dowling, David Chu. 81-88 [doi]
- BioNoculars: Extracting Protein-Protein Interactions from Biomedical TextAmgad Madkour, Kareem Darwish, Hany Hassan, Ahmed Hassan, Ossama Emam. 89-96 [doi]
- A shared task involving multi-label classification of clinical free textJohn P. Pestian, Chris Brew, Pawel Matykiewicz, D. J. Hovermale, Neil Johnson, K. Bretonnel Cohen, Wlodzislaw Duch. 97-104 [doi]
- From indexing the biomedical literature to coding clinical text: experience with MTI and machine learning approachesAlan R. Aronson, Olivier Bodenreider, Dina Demner-Fushman, Kin Wah Fung, Vivian K. Lee, James G. Mork, Aurélie Névéol, Lee B. Peters, Willie J. Rogers. 105-112 [doi]
- Automatically Restructuring Practice Guidelines using the GEM DTDAmanda Bouffier, Thierry Poibeau. 113-120 [doi]
- A Study of Structured Clinical Abstracts and the Semantic Classification of SentencesGrace Chung, Enrico W. Coiera. 121-128 [doi]
- Automatic Code Assignment to Medical TextKoby Crammer, Mark Dredze, Kuzman Ganchev, Partha Pratim Talukdar, Steven Carroll. 129-136 [doi]
- Interpreting comparative constructions in biomedical textMarcelo Fiszman, Dina Demner-Fushman, François-Michel Lang, Philip Goetz, Thomas C. Rindflesch. 137-144 [doi]
- The Extraction of Enriched Protein-Protein Interactions from Biomedical TextBarry Haddow, Michael Matthews. 145-152 [doi]
- What's in a gene name? Automated refinement of gene name dictionariesJörg Hakenberg. 153-160 [doi]
- Exploring the Use of NLP in the Disclosure of Electronic Patient RecordsDavid Hardcastle, Catalina Hallett. 161-162 [doi]
- BaseNPs that contain gene names: domain specificity and genericityIan Lewin. 163-170 [doi]
- Challenges for extracting biomedical knowledge from full textTara McIntosh, James R. Curran. 171-178 [doi]
- Adaptation of POS Tagging for Multiple BioMedical DomainsJohn E. Miller, Manabu Torii, K. Vijay-Shanker. 179-180 [doi]
- Information Extraction from Patients' Free Form DocumentationAgnieszka Mykowiecka, Malgorzata Marciniak. 181-182 [doi]
- Automatic Indexing of Specialized Documents: Using Generic vs. Domain-Specific Document RepresentationsAurélie Névéol, James G. Mork, Alan R. Aronson. 183-190 [doi]
- Developing Feature Types for Classifying Clinical NotesJon Patrick, Yitao Zhang, Yefeng Wang. 191-192 [doi]
- Quantitative Data on Referring Expressions in Biomedical AbstractsMichael Poprat, Udo Hahn. 193-194 [doi]
- Discovering contradicting protein-protein interactions in textOlivia Sanchez-Graillet, Massimo Poesio. 195-196 [doi]
- Marking time in developmental biologyGail Sinclair, Bonnie L. Webber. 197-198 [doi]
- Evaluating and combining and biomedical named entity recognition systemsAndreas Vlachos. 199-200 [doi]
- Unsupervised Learning of the Morpho-Semantic Relationship in MEDLINEW. John Wilbur. 201-208 [doi]
- Reranking for Biomedical Named-Entity RecognitionKazuhiro Yoshida, Jun'ichi Tsujii. 209-216 [doi]