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Recognizing Medication related Entities in Hospital Discharge Summaries using Support Vector Machine

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Figure

Table 1.Number of classes and descriptions with examples in i2b2 2009 dataset.
Figure. 1. An example of the i2b2 data, ‘m’ is for MED NAME, ‘do’ is for DOSE, ‘mo’ is for MODE, ‘f’ is for FREQ, ‘du’ is for DURATION, ‘r’ is for REASON, ‘ln’ is for “list/narrative.”
Figure 2. An example of the BIO representation of annotated clinical text (Where m as medica-tion, do as dose, mo as mode, and f as frequency).
Table 2. Performance of the SVM-based NER system for different feature combinations.

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