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Table 8 Comparison results (%accuracy) on discharge summaries

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)

44.82

51.72

N/A

59.00

65.96

58.91

Maximum Entropy (ME)

48.32

56.34

34.19

58.80

76.10

65.68

Support Vector Machine (SVM)

57.18

62.52

37.22

60.48

80.17

70.46

Conditional Random Field (CRF) [7]

77.33

77.83

48.39

77.47

90.05

83.94

Convolutional Neural Network(CNN) [7]

52.80

65.76

40.00

53.14

79.28

68.60

Bi-RNN model

73.83

79.35

28.00

67.99

82.63

77.85

Transfer learning Bi-RNN model [24]

74.30

82.60

44.00

68.20

86.79

80.75

Our proposed model

76.86

87.22

36.00

71.33

89.20

83.51