Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...

Survival analysis endures as an old, yet active research field with applications that spread across many domains. Continuing improvements in data acquisition techniques pose constant challenges in applying existing survival analysis methods to these emerging data sets. In this paper, we present tools for fitting regularized Cox survival analysis models on high-dimensional, massive sample-size (...

Survival models for life-time data and other time-to-event data are widely used in many fields, including medicine, the environmental sciences, engineering etc., but they have still found less recognition in economics, however they are very helpful in the analysis of economic duration data. This paper provides a reanalysis of the Pennsylvania Reemployment Bonus Experiments, which were conducted...

BACKGROUND The aim of this study was to predict the survival rate of Iranian gastric cancer patients using the Cox proportional hazard and artificial neural network models as well as comparing the ability of these approaches in predicting the survival of these patients. METHODS In this historical cohort study, the data gathered from 436 registered gastric cancer patients who have had surgery ...

In contrast to the Kaplan-Meier method, Cox proportional hazards regression can provide an effect estimate by quantifying the difference in survival between patient groups and can adjust for confounding effects of other variables. The purpose of this article is to explain the basic concepts of the Cox regression method, and to provide some guidance regarding the presentation of the results. Cop...

conclusions the present study detected more accurate results for ann method compared to those of cox ph model to analyze the survival of patients with liver transplantation. furthermore, the order of effective factors in patients’ survival after transplantation was clinically more acceptable. the large dataset with a few missing data was the advantage of this study, the fact which makes the res...

BACKGROUND Survival analysis methods such as the Kaplan-Meier method, log-rank test, and Cox proportional hazards regression (Cox regression) are commonly used to analyze data from randomized withdrawal studies in patients with major depressive disorder. However, unfortunately, such common methods may be inappropriate when a long-term censored relapse-free time appears in data as the methods as...