2010 - Relations

2011
Chapman WW, Nadkarni PM, Hirschman L, D'Avolio LW, Savova GK, Uzuner Ö. Overcoming barriers to NLP for clinical text: the role of shared tasks and the need for additional creative solutions [Internet]. Journal of the American Medical Informatics Association 2011;18(5):540-543. https://doi.org/10.1136/amiajnl-2011-000465
Uzuner Ö, South BR, Shen S, DuVall SL. 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text [Internet]. Journal of the American Medical Informatics Association 2011;18(5):552-556. https://doi.org/10.1136/amiajnl-2011-000203
de Bruijn B, Cherry C, Kiritchenko S, Martin J, Zhu X. Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010 [Internet]. Journal of the American Medical Informatics Association 2011;18(5):557-562. https://doi.org/10.1136/amiajnl-2011-000150
Clark C, Aberdeen J, Coarr M, Tresner-Kirsch D, Wellner B, Yeh A, Hirschman L. MITRE system for clinical assertion status classification [Internet]. Journal of the American Medical Informatics Association 2011;18(5):563-567. https://doi.org/10.1136/amiajnl-2011-000164
Roberts K, Harabagiu SM. A flexible framework for deriving assertions from electronic medical records [Internet]. Journal of the American Medical Informatics Association 2011;18(5):568-573. https://doi.org/10.1136/amiajnl-2011-000152
Patrick JD, Nguyen DHM, Wang Y, Li M. A knowledge discovery and reuse pipeline for information extraction in clinical notes [Internet]. Journal of the American Medical Informatics Association 2011;18(5):574-579. https://doi.org/10.1136/amiajnl-2011-000302
Torii M, Wagholikar K, Liu H. Using machine learning for concept extraction on clinical documents from multiple data sources [Internet]. Journal of the American Medical Informatics Association 2011;18(5):580-587. https://doi.org/10.1136/amiajnl-2011-000155
Minard A-L, Ligozat A-L, Abacha AB, Bernhard D, Cartoni B, Deléger L, Grau B, Rosset S, Zweigenbaum P, Grouin C. Hybrid methods for improving information access in clinical documents: concept, assertion, and relation identification [Internet]. Journal of the American Medical Informatics Association 2011;18(5):588-593. https://doi.org/10.1136/amiajnl-2011-000154
Rink B, Harabagiu S, Roberts K. Automatic extraction of relations between medical concepts in clinical texts [Internet]. Journal of the American Medical Informatics Association 2011;18(5):594-600. https://doi.org/10.1136/amiajnl-2011-000153
Jiang M, Chen Y, Liu M, Rosenbloom TS, Mani S, Denny JC, Xu H. A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries [Internet]. Journal of the American Medical Informatics Association 2011;18(5):601-606. https://doi.org/10.1136/amiajnl-2011-000163
D'Avolio LW, Nguyen TM, Goryachev S, Fiore LD. Automated concept-level information extraction to reduce the need for custom software and rules development [Internet]. Journal of the American Medical Informatics Association 2011;18(5):607-613. https://doi.org/10.1136/amiajnl-2011-000183