Feature Split-based Information Extraction in the Field of Medicine
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[1] Jonathan M. Garibaldi,et al. Automatic detection of protected health information from clinic narratives , 2015, J. Biomed. Informatics.
[2] Li Chen,et al. Supervised methods for symptom name recognition in free-text clinical records of traditional Chinese medicine: An empirical study , 2014, J. Biomed. Informatics.
[3] Li Yang,et al. Exploring feature sets for two-phase biomedical named entity recognition using semi-CRFs , 2013, Knowledge and Information Systems.
[4] Hua Xu,et al. Research and applications: A comprehensive study of named entity recognition in Chinese clinical text , 2014, J. Am. Medical Informatics Assoc..
[5] Li Chen,et al. A Preliminary Work on Symptom Name Recognition from Free-Text Clinical Records of Traditional Chinese Medicine using Conditional Random Fields and Reasonable Features , 2012, BioNLP@HLT-NAACL.
[6] Zhihua Liao,et al. Biomedical Named Entity Recognition Based on Skip-Chain CRFS , 2012, 2012 International Conference on Industrial Control and Electronics Engineering.
[7] Noémie Elhadad,et al. Unsupervised biomedical named entity recognition: Experiments with clinical and biological texts , 2013, J. Biomed. Informatics.
[8] Hua Xu,et al. A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries , 2011, J. Am. Medical Informatics Assoc..
[9] Devanshu Jain,et al. Supervised Named Entity Recognition for Clinical Data , 2015, CLEF.
[10] Bin Fu,et al. The Symptoms and Pathogenesis Entity Recognition of TCM Medical Records Based on CRF , 2015, UIC/ATC/ScalCom.
[11] Yongchao Liu,et al. A framework and its empirical study of automatic diagnosis of traditional Chinese medicine utilizing raw free-text clinical records , 2012, J. Biomed. Informatics.