An enhanced CRFs-based system for information extraction from radiology reports
Authors:
- Andrea EsuliAEAndrea Esuli
- Diego MarcheggianiDMDiego Marcheggiani
- Fabrizio SebastianiFSFabrizio Sebastiani
- 1 June 2013
- journal article
- research article
- Published by Elsevier in Journal of Biomedical Informatics
- Vol. 46 (3) , 425-435
Abstract
No abstract availableKeywords
This publication has 27 references indexed in Scilit:
- An Introduction to Conditional Random FieldsFoundations and Trends in Machine Learning, 2012
- Enhancing clinical concept extraction with distributional semanticsJournal of Biomedical Informatics, 2012
- A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summariesJournal of the American Medical Informatics Association, 2011
- Using machine learning for concept extraction on clinical documents from multiple data sourcesJournal of the American Medical Informatics Association, 2011
- 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical textJournal of the American Medical Informatics Association, 2011
- Extracting medication information from clinical textJournal of the American Medical Informatics Association, 2010
- High accuracy information extraction of medication information from clinical notes: 2009 i2b2 medication extraction challengeJournal of the American Medical Informatics Association, 2010
- Information ExtractionFoundations and Trends® in Databases, 2008
- Evaluating the State-of-the-Art in Automatic De-identificationJournal of the American Medical Informatics Association, 2007
- Information ExtractionQueue, 2005