TMUNSW: Disorder Concept Recognition and Normalization in Clinical Notes for SemEval-2014 Task 7
暂无分享,去创建一个
[1] D. Powers. Evaluation: From Precision, Recall and F-Factor to ROC, Informedness, Markedness & Correlation , 2008 .
[2] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[3] Alan R. Aronson,et al. An overview of MetaMap: historical perspective and recent advances , 2010, J. Am. Medical Informatics Assoc..
[4] 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..
[5] Dietrich Rebholz-Schuhmann,et al. Assessment of disease named entity recognition on a corpus of annotated sentences , 2008, BMC Bioinformatics.
[6] Kent A. Spackman,et al. SNOMED RT: a reference terminology for health care , 1997, AMIA.
[7] Sanna Salanterä,et al. Overview of the ShARe/CLEF eHealth Evaluation Lab 2013 , 2013, CLEF.
[8] Dingcheng Li,et al. Conditional Random Fields and Support Vector Machines for Disorder Named Entity Recognition in Clinical Texts , 2008, BioNLP.
[9] Olivier Bodenreider,et al. The Unified Medical Language System (UMLS): integrating biomedical terminology , 2004, Nucleic Acids Res..
[10] Hua Xu,et al. Recognizing clinical entities in hospital discharge summaries using Structural Support Vector Machines with word representation features , 2013, BMC Medical Informatics and Decision Making.
[11] Jonathan G. Fiscus,et al. A post-processing system to yield reduced word error rates: Recognizer Output Voting Error Reduction (ROVER) , 1997, 1997 IEEE Workshop on Automatic Speech Recognition and Understanding Proceedings.
[12] Matthew Scotch,et al. The Yale cTAKES extensions for document classification: architecture and application , 2011, J. Am. Medical Informatics Assoc..