An Ensemble Learning System Based on Stacking Strategy for Survival Risk Prediction of Patients with Esophageal Cancer
Author:
Ling DanORCID, Jiang Tengfei, Sun Junwei, Wang Yanfeng, Wang Yan, Wang Lidong
Reference31 articles.
1. Xia C, Dong X, Li H, Cao M, Sun D, He S, Yang F, Yan X, Zhang S, Li N, et al., Cancer statistics in china and united states, 2022: profiles, trends, and determinants, Chinese medical journal 135 2. (5) (2022) 584-590, https://doi.org/10.1097/CM9.0000000000002108. 3. Wang Y, Liu Q, Yang Y, Sun J, Wang L, Song X, Zhao X, Prognostic staging of esophageal cancer based on prognosis index and cuckoo search algorithm-support vector machine, Biomedical Signal Processing and Control 79 (2023) 104207, https://doi.org/10.1016/j.bspc.2022.104207. 4. McSorley S. T, Lau H. Y, McIntosh D, Forshaw M. J, McMillan D. C, Crumley A. B, Staging the tumor and staging the host: pretreatment combined neutrophil lymphocyte ratio and modified glasgow prognostic score is associated with overall survival in patients with esophagogastric cancers undergoing treatment with curative intent, Annals of Surgical Oncology 28 (2021) 722–731, https://doi.org/10.1245/s10434-020-09074-5. 5. Huang F, Yu S, Esophageal cancer: risk factors, genetic association, and treatment, Asian journal of surgery 41 (3) (2018) 210–215, https://doi.org/10.1016/j.asjsur.2016.10.005.
|
|