Copyright
©The Author(s) 2016.
World J Radiol. Aug 28, 2016; 8(8): 729-734
Published online Aug 28, 2016. doi: 10.4329/wjr.v8.i8.729
Published online Aug 28, 2016. doi: 10.4329/wjr.v8.i8.729
Table 3 Mean number of predicted solitary pulmonary nodules for each risk class considered, before (pre-computer-aided diagnosis) and after (post-computer-aided diagnosis) computer-aided diagnosis result disclosure
| Risk class | Benign SPNs | Malignant SPNs | ||
| Pre-CAD | Post-CAD | Pre-CAD | Post-CAD | |
| 1 | 6.71 | 13.43 | 1.86 | 1.86 |
| 2 | 12.43 | 6.86 | 8.43 | 7.14 |
| 3 | 6.43 | 3.71 | 17.43 | 11.29 |
| 4 | 3.57 | 5.00 | 15.29 | 15.57 |
| 5 | 2.86 | 3.00 | 19.00 | 26.14 |
- Citation: Perandini S, Soardi GA, Motton M, Augelli R, Dallaserra C, Puntel G, Rossi A, Sala G, Signorini M, Spezia L, Zamboni F, Montemezzi S. Enhanced characterization of solid solitary pulmonary nodules with Bayesian analysis-based computer-aided diagnosis. World J Radiol 2016; 8(8): 729-734
- URL: https://www.wjgnet.com/1949-8470/full/v8/i8/729.htm
- DOI: https://dx.doi.org/10.4329/wjr.v8.i8.729