Table 1 Experimental results
From: Ontology boosted deep learning for disease name extraction from Twitter messages
Methods | Measure | Data set | |
|---|---|---|---|
Mumps + measles + pneumonia | Pink eye | ||
CNF + log linear model | Precision | 0.68 | 0.71 |
Recall | 0.43 | 0.58 | |
F measure | 0.53 | 0.64 | |
CNF + CRF | Precision | 0.79 | 0.68 |
Recall | 0.58 | 0.63 | |
F measure | 0.67 | 0.65 | |
LSTM + custom Word2Vecmodel | Precision | 0.00 | 0.74 |
Recall | 0.00 | 0.05 | |
F measure | 0.00 | 0.02 | |
LSTM + generic Word2Vec model | Precision | 0.55 | 0.35 |
Recall | 0.04 | 0.17 | |
F measure | 0.08 | 0.23 | |
LSTM + CNF Word2Vec | Precision | 0.78 | 0.71 |
Recall | 0.67 | 0.82 | |
F measure | 0.72 | 0.77 | |