Copyright
©The Author(s) 2024.
World J Gastroenterol. Oct 28, 2024; 30(40): 4354-4366
Published online Oct 28, 2024. doi: 10.3748/wjg.v30.i40.4354
Published online Oct 28, 2024. doi: 10.3748/wjg.v30.i40.4354
Figure 4 Performance in the four subgroups when XGBoost is used to predict the patient’s overall survival and progression-free survival.
A: The performance of XGBoost in predicting overall survival for female patients, male patients, non-surgically treated patients, and surgically treated patients; B: The performance of XGBoost in predicting progression-free survival for female patients, male patients, non-surgically treated patients, and surgically treated patients. NPV: Negative predictive value; PPV: Positive predictive value.
- Citation: Li HW, Zhu ZY, Sun YF, Yuan CY, Wang MH, Wang N, Xue YW. Machine learning algorithms able to predict the prognosis of gastric cancer patients treated with immune checkpoint inhibitors. World J Gastroenterol 2024; 30(40): 4354-4366
- URL: https://www.wjgnet.com/1007-9327/full/v30/i40/4354.htm
- DOI: https://dx.doi.org/10.3748/wjg.v30.i40.4354