Copyright
©The Author(s) 2023.
World J Orthop. Oct 18, 2023; 14(10): 741-754
Published online Oct 18, 2023. doi: 10.5312/wjo.v14.i10.741
Published online Oct 18, 2023. doi: 10.5312/wjo.v14.i10.741
Figure 5 Receiver operating characteristic curve for machine learning models after cross-validation.
ROC: Receiver operating characteristic; LR: Logistic regression; DT: Decision tree; RF: Random forest; SVC: Support vector classifier; NB: Naïve bayes; KNN: K-nearest Neighbour; XGB: eXtreme Gradient Boosting; ANN: Artificial neural network.
- Citation: Tian CW, Chen XX, Shi L, Zhu HY, Dai GC, Chen H, Rui YF. Machine learning applications for the prediction of extended length of stay in geriatric hip fracture patients. World J Orthop 2023; 14(10): 741-754
- URL: https://www.wjgnet.com/2218-5836/full/v14/i10/741.htm
- DOI: https://dx.doi.org/10.5312/wjo.v14.i10.741