Table 4.
Method | Year | Dataset | AUC | Accuracy | Sensitivity | Specificity |
---|---|---|---|---|---|---|
Thi Kieu Khanh Ho et al. [19] | 2019 | Shenzhen | 0.914 | — | — | — |
Montgomery | 0.939 | — | — | — | ||
Satyavratan et al. [12] | 2019 | Montgomery | 0.94 | 0.878 | 0.877 | 0.859 |
| ||||||
Sivaramakrishnan et al. [18] | 2018 | Shenzhen | 0.926 | 0.855 | — | — |
Montgomery | 0.833 | 0.758 | — | — | ||
Mohammad et al. [21] | 2017 | Shenzhen | 0.940 | 0.900 | 0.88 | 0.92 |
| ||||||
Lopes et al. [17] | 2017 | Shenzhen | 0.926 | 0.847 | — | — |
Montgomery | 0.926 | 0.826 | — | — | ||
| ||||||
Sangheum Hwang et al. [20] | 2016 | Shenzhen | 0.926 | 0.837 | — | — |
Montgomery | 0.884 | 0.674 | — | — | ||
| ||||||
Our method | 2019 | Shenzhen | 0.941 | 0.902 | 0.854 | 0.951 |
Montgomery | 0.977 | 0.926 | 0.931 | 0.923 | ||
Local | 0.993 | 0.974 | 0.983 | 0.962 |