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Table 6 Performance comparison of different algorithms

From: A deep learning model incorporating part of speech and self-matching attention for named entity recognition of Chinese electronic medical records

  P R F1
N-gram-Based RNN-CRF [23] 0.5254 0.4056 0.4578
Character-Based LSTM-CRF [11] 0.6568 0.6904 0.6732
Attention-Based CNN-LSTM-CRF [21] 0.7224 0.7248 0.7236
SM-LSTM-CRF 0.8054 0.7961 0.8007