Table 1.
Summary of computer-aided diagnostic models in mammography interpretation.
| Study (year) | Size of dataset (n) |
Model | AUC | Reader study |
Ref. |
|---|---|---|---|---|---|
| Jiang et al. (1996) | 107 | ANN | 0.92 | Yes | [26] |
| Markopoulos et al. (2001) | 240 | ANN | 0.937 | Yes | [31] |
| Huo et al. (2002) | 110 | ANN | 0.96 | Yes | [35] |
| Floyd et al. (2000) | 500 | CBR | 0.83 | No | [37] |
| Elter et al. (2007) | 2100 | DT/CBR | 0.87/0.89 | No | [38] |
| Chan et al. (1999) | 253 | LDC | 0.91 | Yes | [34] |
| Gupta et al. (2006) | 115 | LDA | 0.92 | No | [41] |
| Wang et al. (1999) | 419 | BN | 0.886 | No | [42] |
| Chhatwal et al. (2009) | 62,219 | LR | 0.963 | Yes | [43] |
| Burnside et al. (2009) | 62,219 | BN | 0.960 | Yes | [44] |
| Ayer et al. (2010) | 62,219 | ANN | 0.965 | Yes | [45] |
| Bilska-Wolak et al. (2005) | 151 | LRbC | 0.88 | No | [46] |
ANN: Artificial neural network; AUC: Area under the curve; BN: Bayesian network; CBR: Case-based reasoning; DT: Decision tree; LDA: Linear discriminant analysis; LDC: Linear discriminant classifier; LR: Logistic regression; LRbC: Likelihood ratio-based classifier.