Conditional Random Fields and Support Vector Machines for Disorder Named Entity Recognition in Clinical Texts
نویسندگان
چکیده
We present a comparative study between two machine learning methods, Conditional Random Fields and Support Vector Machines for clinical named entity recognition. We explore their applicability to clinical domain. Evaluation against a set of gold standard named entities shows that CRFs outperform SVMs. The best F-score with CRFs is 0.86 and for the SVMs is 0.64 as compared to a baseline of 0.60.
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تاریخ انتشار 2008