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Table 9 Comparison results (%accuracy) on progress notes

From: A multitask bi-directional RNN model for named entity recognition on Chinese electronic medical records

Model

Entity type

 

Disease

Symptom

Disease group

Treatment

Test

Overall accuracy

Naive Bayes (NB)

69.50

70.09

N/A

41.59

71.85

67.49

Maximum Entropy (ME)

71.49

72.37

41.15

52.93

77.58

72.44

Support Vector Machine (SVM)

77.77

76.92

21.12

56.36

81.49

76.45

Conditional Random Field (CRF) [7]

87.42

87.09

36.06

75.60

90.31

87.22

Convolutional Neural Network(CNN) [7]

76.19

76.65

12.50

51.83

76.65

73.40

Bi-RNN model

87.48

87.01

25.00

63.99

83.75

82.72

Transfer learning Bi-RNN model [24]

88.70

88.49

31.25

72.93

86.12

85.43

Our proposed model

92.24

94.19

75.00

86.46

92.61

92.13