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©The Author(s) 2022.
World J Clin Cases. Apr 26, 2022; 10(12): 3729-3738
Published online Apr 26, 2022. doi: 10.12998/wjcc.v10.i12.3729
Published online Apr 26, 2022. doi: 10.12998/wjcc.v10.i12.3729
Table 3 Multivariate logistic regression model for top 10 variables in random forest
Variables | Odds ratio (95%CI) | P value |
Age | 1.56 (0.57-5.87) | 0.04 |
Body mass index | 2.83 (0.68-5.54) | 0.02 |
Ischemia time | 1.98 (0.53-3.24) | 0.001 |
Smoking | 1.13 (0.28-2.89) | 0.87 |
Diabetes | 1.15 (0.53-3.28) | 0.06 |
Experience | 0.86 (0.18-4.87) | 0.79 |
Prior chemotherapy | 1.15 (0.56-2.68) | 0.07 |
Hypertension | 1.08 (0.25-2.64) | 0.28 |
Insulin | 1.27 (0.64-3.21) | 0.54 |
Obesity | 1.09 (0.57-2.95) | 0.13 |
- Citation: Shi YC, Li J, Li SJ, Li ZP, Zhang HJ, Wu ZY, Wu ZY. Flap failure prediction in microvascular tissue reconstruction using machine learning algorithms. World J Clin Cases 2022; 10(12): 3729-3738
- URL: https://www.wjgnet.com/2307-8960/full/v10/i12/3729.htm
- DOI: https://dx.doi.org/10.12998/wjcc.v10.i12.3729