Research Article
TCMNER and PubMed: A Novel Chinese Character-Level-Based Model and a Dataset for TCM Named Entity Recognition
Table 5
The performances of different models in the test set of publications and the entire medical records.
| % | Publications (test) | Medical records | P | R | F1 | P | R | F1 |
| BiLSTM-CRF | 60.8 | 30.6 | 40.7 | 61.4 | 48.3 | 54.1 | BERT-CRF | 58.7 | 54.2 | 56.4 | 54.7 | 60.5 | 57.4 | BERT-BiLSTM | 93 | 91.6 | 90.3 | 85.5 | 88.1 | 86.8 | BERT-BiLSTM-CRF | 75.4 | 73.1 | 74.2 | 69 | 75.2 | 71.9 | RoBERTa-BiLSTM | 88.8 | 92.6 | 90.7 | 86.3 | 90.1 | 88.2 | RoBERTa-c | 92.6 | 96.7 | 94.6 | 90.4 | 92.3 | 91.3 |
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