Research Article
[Retracted] BJBN: BERT-JOIN-BiLSTM Networks for Medical Auxiliary Diagnostic
Table 2
Experimental results of eight models with TCM data.
| | Model | Average acc | Average precision | Average recall | Average F1-score |
| | FastText | 0.6628 | 0.7520 | 0.5866 | 0.6592 | | TextCNN | 0.6243 | 0.7362 | 0.5621 | 0.6375 | | TextRNN | 0.6521 | 0.7456 | 0.5697 | 0.6459 | | TextRCNN | 0.6957 | 0.7672 | 0.6238 | 0.6881 | | DPCNN | 0.6139 | 0.6692 | 0.5873 | 0.6256 | | TextRNN_Att | 0.7153 | 0.7749 | 0.6477 | 0.7056 | | Transformer | 0.6285 | 0.6837 | 0.5891 | 0.6329 | | Our model | 0.7512 | 0.8352 | 0.6818 | 0.7569 |
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