Publications

Prediction of Prognosis and Survival of Patients with Gastric Cancer by Weighted Improved Random Forest Model
Cheng Xu, Jing Wang, TianLong Zheng, Yue Cao, Fan Ye.
Archives of Medical Science 2021
[Paper] / [PDF] / [PubMed]
We propose a new Random Forest weighting method and apply it to the gastric cancer patient data from the Surveillance, Epidemiology, and End Results (SEER) program, and then evaluated the generalization ability of this weighted Random Forest algorithm on 10 public medical datasets. Furthermore, for the same weighting mode, the difference between using out-of-bag (OOB) data and all training sets as the weighting basis is explored.

Selection of surgical procedures and analysis of prognostic factors in patients with primary gastric tumour based on Cox regression: a SEER database analysis based on data mining
Cheng Xu, Qingling Chen, Fan Ye, Qi Fan, Qing Wang.
Gastroenterology Review 2021
[Paper] / [PDF] / [PubMed]
In order to explore the cause of gastric cancer, we analysed the data from the SEER database and obtained some valuable information. The contents of our study are as follows: the effects of various physical indicators on the incidence of gastric cancer, the differences of different type of surgery for patients with different stages, and the differences of the different type of surgery for the same operation.