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 3 Shapley additive explanations summary plots of each model.
A: Logistic regression; B: Decision tree; C: Random forest; D: Support vector classifier; E: Naïve bayes; F: K-nearest neighbour; G: eXtreme Gradient Boosting; H: Artificial neural network. ASA: American society of anaesthesiologists; THA: Total hip arthroplasty; DVT: Deep venous thrombosis; AST: Aspartate aminotransferase.
- 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