Copyright
©The Author(s) 2022.
World J Clin Cases. Jan 14, 2022; 10(2): 518-527
Published online Jan 14, 2022. doi: 10.12998/wjcc.v10.i2.518
Published online Jan 14, 2022. doi: 10.12998/wjcc.v10.i2.518
Table 2 Diagnostic efficiency of four diagnostic models
| Inspection method | Pathology | Susceptibility (%) | Specificity (%) | Accuracy (%) | Jordan index | Positive predictive value (%) | Negative predictive value (%) | |
| Benign | Malignant | |||||||
| Conventional ultrasound BI-RADS classification | 84.78 | 57.21 | 74.44 | 0.5199 | 61.11 | 85.42 | ||
| Benign (n = 48) | 41 | 7 | ||||||
| Malignant (n = 59) | 20 | 39 | ||||||
| AI-SONIC Breast system | 86.96 | 75.41 | 80.37 | 0.6237 | 72.73 | 88.46 | ||
| Benign (n = 52) | 46 | 6 | ||||||
| Malignant (n = 53) | 15 | 40 | ||||||
| AI-SONIC Breast system combined BI-RADS classification of conventional ultrasound | 80.43 | 90.16 | 85.98 | 0.7059 | 86.05 | 85.94 | ||
| Benign (n = 64) | 55 | 9 | ||||||
| Malignant (n = 43) | 6 | 37 | ||||||
| Adjusted BI-RADS classification | 93.48 | 67.21 | 78.50 | 0.6069 | 68.25 | 93.18 | ||
| Benign (n = 44) | 41 | 3 | ||||||
| Malignant (n = 63) | 20 | 43 | ||||||
- Citation: Lyu SY, Zhang Y, Zhang MW, Zhang BS, Gao LB, Bai LT, Wang J. Diagnostic value of artificial intelligence automatic detection systems for breast BI-RADS 4 nodules. World J Clin Cases 2022; 10(2): 518-527
- URL: https://www.wjgnet.com/2307-8960/full/v10/i2/518.htm
- DOI: https://dx.doi.org/10.12998/wjcc.v10.i2.518