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Table 3 Comparison between a series of CLSTM (contextual long short-term memory networks [LSTMs] with conditional random fields [CRF]) experiments and the comparative methods on the NCBI, GM, and CDR corpora using strict matching

From: Biomedical named entity recognition using deep neural networks with contextual information

Strict matching

NCBI

GM

CDR

Model

Trial #

p

r

f

p

r

f

p

r

f

BiLSTM

-

78.91

82.60

80.71

72.22

72.44

72.33

83.56

80.26

81.88

BiLSTM-CRF

-

82.19

84.58

83.37

80.79

79.81

80.30

87.52

83.58

85.50

GRAM-CNN

-

84.45

83.92

84.18

80.23

78.83

79.53

86.08

85.49

85.79

BERT

-

81.07

80.73

80.90

81.72

81.59

81.65

86.21

85.23

85.72

CLSTM (word+char levels)

1

84.73

86.67

85.68

81.75

81.14

81.44

87.25

85.66

86.44

 

2

84.43

85.83

85.12

81.26

80.67

80.96

87.16

85.40

86.27

 

3

86.18

84.48

85.32

82.07

80.24

81.14

87.93

84.56

86.21

 

4

85.56

85.21

85.39

82.97

79.66

81.28

87.71

85.17

86.42

 

5

84.62

85.42

85.02

81.02

80.70

80.86

88.27

84.36

86.27

CLSTM average

 

85.10

85.52

85.31

81.81

80.48

81.14

87.66

85.03

86.33