title: Comparison between artificial neural network and Cox regression model in predicting the survival rate of gastric cancer patients.
abstract: The aim of this study was to determine the prognostic factors and their significance in gastric cancer (GC) patients, using the artificial neural network (ANN) and Cox regression hazard (CPH) models. A retrospective analysis was undertaken, including 289 patients with GC who had undergone gastrectomy between 2006 and 2007. According to the CPH analysis, disease stage, peritoneal dissemination, radical surgery and body mass index (BMI) were selected as the significant variables. According to the ANN model, disease stage, radical surgery, serum CA19-9 levels, peritoneal dissemination and BMI were selected as the significant variables. The true prediction of the ANN was 85.3% and of the CPH model 81.9%. In conclusion, the present study demonstrated that the ANN model is a more powerful tool in determining the significant prognostic variables for GC patients, compared to the CPH model. Therefore, this model is recommended for determining the risk factors of such patients.
authors.affiliation: Department of Radio-Chemotherapy Oncology, The First Affiliated Hospital of Wenzhou Medical College, Wenzhou, Zhejiang 325002, P.R. China.
authors.forename: Lucheng
authors.initials: L
authors.lastname: Zhu
authors.affiliation: Department of Radio-Chemotherapy Oncology, The First Affiliated Hospital of Wenzhou Medical College, Wenzhou, Zhejiang 325002, P.R. China.
authors.forename: Wenhua
authors.initials: W
authors.lastname: Luo
authors.affiliation: Department of Radio-Chemotherapy Oncology, The First Affiliated Hospital of Wenzhou Medical College, Wenzhou, Zhejiang 325002, P.R. China.
authors.forename: Meng
authors.initials: M
authors.lastname: Su
authors.affiliation: Department of Radio-Chemotherapy Oncology, The First Affiliated Hospital of Wenzhou Medical College, Wenzhou, Zhejiang 325002, P.R. China.
authors.forename: Hangping
authors.initials: H
authors.lastname: Wei
authors.affiliation: Department of Radio-Chemotherapy Oncology, The First Affiliated Hospital of Wenzhou Medical College, Wenzhou, Zhejiang 325002, P.R. China.
authors.forename: Juan
authors.initials: J
authors.lastname: Wei
authors.affiliation: Department of Radio-Chemotherapy Oncology, The First Affiliated Hospital of Wenzhou Medical College, Wenzhou, Zhejiang 325002, P.R. China.
authors.forename: Xuebang
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Department of Radio-Chemotherapy Oncology, The First Affiliated Hospital of Wenzhou Medical College, Wenzhou, Zhejiang 325002, P.R. China.
authors.forename: Changlin
authors.initials: C
authors.lastname: Zou
keywords: Cox regression hazard; artificial neural network; gastric cancer/carcinoma; multivariate analysis; prognosis