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Syntactic complexity measures for detecting Mild Cognitive Impairment
Brian Roark, Margaret Mitchell and Kristy Hollingshead |
pp. 1–8 |
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Determining the Syntactic Structure of Medical Terms in Clinical Notes
Bridget McInnes, Ted Pedersen and Serguei Pakhomov |
pp. 9–16 |
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The Role of Roles in Classifying Annotated Biomedical Text
Son Doan, Ai Kawazoe and Nigel Collier |
pp. 17–24 |
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On the unification of syntactic annotations under the Stanford dependency scheme: A case study on BioInfer and GENIA
Sampo Pyysalo, Filip Ginter, Veronika Laippala, Katri Haverinen, Juho Heimonen and Tapio Salakoski |
pp. 25–32 |
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An Unsupervised Method for Extracting Domain-specific Affixes in Biological Literature
Haibin Liu, Christian Blouin and Vlado Keselj |
pp. 33–40 |
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Combining multiple evidence for gene symbol disambiguation
Hua Xu, Jung-Wei Fan and Carol Friedman |
pp. 41–48 |
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Mining a Lexicon of Technical Terms and Lay Equivalents
Noemie Elhadad and Komal Sutaria |
pp. 49–56 |
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Annotation of Chemical Named Entities
Peter Corbett, Colin Batchelor and Simone Teufel |
pp. 57–64 |
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Recognising Nested Named Entities in Biomedical Text
Beatrice Alex, Barry Haddow and Claire Grover |
pp. 65–72 |
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Exploring the Efficacy of Caption Search for Bioscience Journal Search Interfaces
Marti Hearst, Anna Divoli, Ye Jerry and Michael Wooldridge |
pp. 73–80 |
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ConText: An Algorithm for Identifying Contextual Features from Clinical Text
Wendy Chapman, John Dowling and David Chu |
pp. 81–88 |
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BioNoculars: Extracting Protein-Protein Interactions from Biomedical Text
Amgad Madkour, Kareem Darwish, Hany Hassan, Ahmed Hassan and Ossama Emam |
pp. 89–96 |
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A shared task involving multi-label classification of clinical free text
John P. Pestian, Chris Brew, Pawel Matykiewicz, DJ Hovermale, Neil Johnson, K. Bretonnel Cohen and Wlodzislaw Duch |
pp. 97–104 |
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From indexing the biomedical literature to coding clinical text: experience with MTI and machine learning approaches
Alan R. Aronson, Olivier Bodenreider, Dina Demner-Fushman, Kin Wah Fung, Vivian K. Lee, James G. Mork, Aurelie Neveol, Lee Peters and Willie J. Rogers |
pp. 105–112 |
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Automatically Restructuring Practice Guidelines using the GEM DTD
Amanda Bouffier and Thierry Poibeau |
pp. 113–120 |
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A Study of Structured Clinical Abstracts and the Semantic Classification of Sentences
Grace Chung and Enrico Coiera |
pp. 121–128 |
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Automatic Code Assignment to Medical Text
Koby Crammer, Mark Dredze, Kuzman Ganchev, Partha Pratim Talukdar and Steven Carroll |
pp. 129–136 |
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Interpreting comparative constructions in biomedical text
Marcelo Fiszman, Dina Demner-Fushman, Francois M. Lang, Philip Goetz and Thomas C. Rindflesch |
pp. 137–144 |
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The Extraction of Enriched Protein-Protein Interactions from Biomedical Text
Barry Haddow and Michael Matthews |
pp. 145–152 |
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What’s in a gene name? Automated refinement of gene name dictionaries
Jörg Hakenberg |
pp. 153–160 |
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Exploring the Use of NLP in the Disclosure of Electronic Patient Records
David Hardcastle and Catalina Hallett |
pp. 161–162 |
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BaseNPs that contain gene names: domain specificity and genericity
Ian Lewin |
pp. 163–170 |
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Challenges for extracting biomedical knowledge from full text
Tara McIntosh and James R. Curran |
pp. 171–178 |
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Adaptation of POS Tagging for Multiple BioMedical Domains
John E. Miller, Manabu Torii and K. Vijay-Shanker |
pp. 179–180 |
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Information Extraction from Patients’ Free Form Documentation
Agnieszka Mykowiecka and Malgorzata Marciniak |
pp. 181–182 |
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Automatic Indexing of Specialized Documents: Using Generic vs. Domain-Specific Document Representations
Aurelie Neveol, James G. Mork and Alan R. Aronson |
pp. 183–190 |
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Developing Feature Types for Classifying Clinical Notes
Jon Patrick, Yitao Zhang and Yefeng Wang |
pp. 191–192 |
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Quantitative Data on Referring Expressions in Biomedical Abstracts
Michael Poprat and Udo Hahn |
pp. 193–194 |
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Discovering contradicting protein-protein interactions in text
Olivia Sanchez and Massimo Poesio |
pp. 195–196 |
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Marking time in developmental biology
Gail Sinclair and Bonnie Webber |
pp. 197–198 |
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Evaluating and combining and biomedical named entity recognition systems
Andreas Vlachos |
pp. 199–200 |
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Unsupervised Learning of the Morpho-Semantic Relationship in MEDLINE
W. John Wilbur |
pp. 201–208 |
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Reranking for Biomedical Named-Entity Recognition
Kazuhiro Yoshida and Jun’ichi Tsujii |
pp. 209–216 |
Last modified on May 29, 2007, 9:05 p.m.