Bidirectional LSTM-CRF for Clinical Concept Extraction
Table 3: Performance comparison between the bidirectional LSTM-CRF (bottom three lines) and state-of-the-art systems (top five lines) over the 2010 i2b2/VA concept extraction task.
['Methods', 'Precision', 'Recall', 'F1 Score']
As a first note, the bidirectional LSTM-CRF initialized with GloVe outperforms all recent approaches (2012-2015). Using general-purpose, pre-trained embeddings improves the F1 score by over 5 percentage points over a random initialization. In general, the results achieved with the proposed approach are close and in many cases above the results achieved by systems based on hand-engineered features.