Table 3.
Clinical NER: impact of distributional semantic features.
| Setting | Exact F | Inexact F | Exact increase | Inexact increase |
|---|---|---|---|---|
| MED_noDict | 79.4 | 89.2 | ||
| MED_Dict | 80.3 | 89.7 | 0.9 | 0.5 |
| MED_noDict+NN+SVM | 81.4 | 90.8 | 2.0 | 1.6 |
| MED_Dict+NN+SVM | 81.9 | 91.0 | 2.5 | 1.8 |
Notes: MED_noDict is the machine-learning clinical NER system with all the sentence-level orthographic and syntactic features, but no features from lexicons such as UMLS, Drugs@FDA, and MedDRA. MED_noDict+NN+SVM also has the features generated using SVM and the nearest neighbors algorithm.