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Table 4 Medical event detection accuracy of our sequence labelling models on the test set

From: An approach for medical event detection in Chinese clinical notes of electronic health records

  Model Acc.
Text classification models bi-LSTM(1 layer) 82.4%
  bi-LSTM(2 layers) 84.2%
  bi-LSTM(3 layers) 83.1%
  text-CNN 85.8%
Sequence labelling models bi-LSTM(2 layers) feature extractor + bi-LSTM decoder 87.3%
  bi-LSTM(2 layers) feature extractor + smoothed Viterbi decoder 87.4%
  bi-LSTM(2 layers) feature extractor + CRF decoder 92.1%
  CNNs feature extractor + bi-LSTM decoder 89.9%
  CNNs feature extractor + smoothed Viterbi decoder 90.7%
  CNNs feature extractor + CRF decoder 92.6%
  1. The bold font means the best result