- Detecting concept relations in clinical text: insights from a state-of-the-art modelXiaodan Zhu
Institute for Information Technology, National Research Council Canada, 1200 Montreal Road, Ottawa, ON, Canada K1A 0R6
J Biomed Inform 46:275-85. 2013..As the second major objective, we reformulate our models into a composite-kernel framework and present the best result, according to our knowledge, on the same dataset...
- Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010Berry de Bruijn
Institute for Information Technology, National Research Council, Ottawa, Ontario, Canada
J Am Med Inform Assoc 18:557-62. 2011..In this paper, the authors describe the design and performance of three state-of-the-art text-mining applications from the National Research Council of Canada on evaluations within the 2010 i2b2 challenge...
- A la Recherche du Temps Perdu: extracting temporal relations from medical text in the 2012 i2b2 NLP challengeColin Cherry
Information and Communication Technologies, National Research Council Canada, Ottawa, Ontario, Canada
J Am Med Inform Assoc 20:843-8. 2013..The 2012 i2b2 NLP challenge focused on the extraction of temporal relationships between concepts within textual hospital discharge summaries...