Copyright
©The Author(s) 2023.
World J Gastroenterol. May 21, 2023; 29(19): 2979-2991
Published online May 21, 2023. doi: 10.3748/wjg.v29.i19.2979
Published online May 21, 2023. doi: 10.3748/wjg.v29.i19.2979
Indicators (95%CI) | Testing set, n = 291 | P value | Validation set, n = 197 | P value |
Sensitivity | 0.931 (0.859-0.970) | 0.046 | 0.836 (0.727-0.909) | 0.522 |
Specificity | 0.079 (0.047-0.130) | < 0.001 | 0.073 (0.036-0.137) | < 0.001 |
PPV | 0.353 (0.297-0.414) | < 0.001 | 0.347 (0.278-0.422) | < 0.001 |
NPV | 0.682 (0.451-0.853) | 0.004 | 0.429 (0.226-0.656) | < 0.001 |
Accuracy | 0.378 (0.323-0.437) | < 0.001 | 0.355 (0.289-0.427) | < 0.001 |
- Citation: Wang Z, Shao SL, Liu L, Lu QY, Mu L, Qin JC. Machine learning model for prediction of low anterior resection syndrome following laparoscopic anterior resection of rectal cancer: A multicenter study. World J Gastroenterol 2023; 29(19): 2979-2991
- URL: https://www.wjgnet.com/1007-9327/full/v29/i19/2979.htm
- DOI: https://dx.doi.org/10.3748/wjg.v29.i19.2979