Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010

Author:

de Bruijn Berry,Cherry Colin,Kiritchenko Svetlana,Martin Joel,Zhu Xiaodan

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

Reference17 articles.

1. 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text

2. Savova G Kipper-Schuler K Buntrock J . UIMA-based clinical information extraction system. In: Proceedings of The Sixth International Conference on Language Resources and Evaluation: Workshop on Towards Enhanced Interoperability for Large HLT Systems: UIMA for NLP. Marrakech, Morocco: Language Resources and Evaluation Conference, 2008:39–42.

3. An overview of MetaMap: historical perspective and recent advances

4. ConText: An algorithm for determining negation, experiencer, and temporal status from clinical reports

5. Miller S Guinness J Zamanian A . Name tagging with word clusters and discriminative training. In: Proceedings of Human Language Technology Conference / North American Chapter of the Association for Computational Linguistics Annual Meeting. Boston, MA, USA: Association for Computational Linguistics, 2004;337–42.

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