Copyright
©The Author(s) 2025.
World J Hepatol. Mar 27, 2025; 17(3): 97767
Published online Mar 27, 2025. doi: 10.4254/wjh.v17.i3.97767
Published online Mar 27, 2025. doi: 10.4254/wjh.v17.i3.97767
Table 3 Positive predictive and negative predictive values, 95%CI
| Cohort | Models | 3-year risk of PVT | 5-year risk of PVT | ||
| Positive (%) | Negative (%) | Positive (%) | Negative (%) | ||
| Training cohort | ANN (low risk) | 26.2 (25.0-27.4) | 98.7 (95.2-99.7) | 23.2 (21.0-28.4) | 97.7 (95.2-99.7) |
| ANN (high risk) | 54.7 (48.6-60.7) | 98.6 (89.4-99.4) | 52.7 (49.6-60.7) | 98.6 (88.4-99.5) | |
| Validation cohort | ANN (low risk) | 20.9 (19.6-22.2) | 100 (-) | 19.9 (19.6-24.2) | 97.9 (89.6-98.3) |
| ANN (high risk) | 41.5 (32.8-50.8) | 91.9 (88.6-94.3) | 31.5 (28.8-51.8) | 98.9 (88.6-99.3) | |
- Citation: Meng PP, Xiong FX, Chen JL, Zhou Y, Liu XL, Ji XM, Jiang YY, Hou YX. Establish and validate an artificial neural networks model used for predicting portal vein thrombosis risk in hepatitis B-related cirrhosis patients. World J Hepatol 2025; 17(3): 97767
- URL: https://www.wjgnet.com/1948-5182/full/v17/i3/97767.htm
- DOI: https://dx.doi.org/10.4254/wjh.v17.i3.97767