Table 4 Characteristics of the prevalence of accuracy of AI in caries detection

1

Chen et al. 2023 [17]

11,000

95.44%

0.99

1.00

1.000

 < 0.001

2

Zhu et al. 2022 [18]

1159

93.61%

0.94

0.97

0.959

 < 0.001

3

Bayraktar et al. 2022 [19]

1000

94.59%

0.96

0.99

0.982

 < 0.001

4

Huang et al. 2021 [20]

748

95.21%

0.98

1.01

0.997

 < 0.001

5

Mao et al. 2021 [21]

278

95.56%

0.98

1.03

1.008

 < 0.001

6

De Araujo Faria et al. 2021 [22]

15

98.8%

1.25

1.34

1.303

0.001

7

Vinayahalingam et al. 2021 [25]

500

87.0%

0.36

0.39

0.381

0.046

8

Moran et al

2021 [27]

112

73.3%

0.046

0.058

0.052

 < 0.001

9

Lian et al

2021 [28]

1160

98.6%

1.45

1.47

1.469

 < 0.001

10

Zheng et al

2021 [29]

844

82.0%

0.29

0.30

0.300

 < 0.001

11

Geetha et al

2020 [33]

145

97.1%

1.21

1.28

1.246

 < 0.001

12

Cantu et al

2020 [34]

3293

80.0%

0.30

0.31

0.312

 < 0.001

13

Lee et al

2018 [36]

3000

89.0%

0.47

0.48

0.479

0.080

14

Srivastava et al

2017 [37]

3000

80.5%

0.29

0.30

0.303

 < 0.001