Copyright
©The Author(s) 2020.
World J Gastroenterol. Aug 21, 2020; 26(31): 4607-4623
Published online Aug 21, 2020. doi: 10.3748/wjg.v26.i31.4607
Published online Aug 21, 2020. doi: 10.3748/wjg.v26.i31.4607
Table 3 The efficiency of the diagnostic model
| Model | Accuracy (%) | Sensitivity (%) | Specificity (%) | Positive predictive value | Negative predictive value | ROC-AUC (95%CI) | P value | |
| Training set | LDA | 95.00 | 100.00 | 90.00 | 0.91 | 1.00 | 0.90 (0.81-0.99) | < 0.05 |
| AFP | 65.00 | 30.00 | 100.00 | 1.00 | 0.59 | 0.69 (0.52-0.86) | ||
| Validation set | LDA | 78.95 | 100.00 | 60.00 | 0.69 | 1.00 | 0.84 (0.67-1.00) | < 0.05 |
| AFP | 68.42 | 40.00 | 100.00 | 1.00 | 0.60 | 0.68 (0.41-0.94) | ||
- Citation: Zhou PC, Sun LQ, Shao L, Yi LZ, Li N, Fan XG. Establishment of a pattern recognition metabolomics model for the diagnosis of hepatocellular carcinoma. World J Gastroenterol 2020; 26(31): 4607-4623
- URL: https://www.wjgnet.com/1007-9327/full/v26/i31/4607.htm
- DOI: https://dx.doi.org/10.3748/wjg.v26.i31.4607