gastric cancer is the most prevalent cancer among men and the third most prevalent cancer among women in iran. its most important reason for death is its belated diagnosis at the advanced stages of the disease. various factors can be effective on the survival of these patients after surgery, which are the major concern in this study.data from 330 patients with gastric cancer who had undergone s...

conclusions by controlling the modifiable risk factors and modality of treatment in our study, physicians can reach more effective treatment. results at the end of the study, long-term graft failure was seen in 27 (10.2%) cases. one-year and 2-year graft survival after diagnosis of cancer were 93.6% and 91.7%, respectively. the univariate analysis showed that the incidence of chronic graft loss...

results survival probabilities at different times were determined using the cox proportional hazards and a neural network with three nodes in the hidden layer; the ratios of standard errors with these two methods to the kaplan-meier method were 1.1593 and 1.0071, respectively, revealed a significant difference between cox and kaplan-meier (p < 0.05) and no significant difference between cox and...

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...

Cox's proportional hazards model is often t to grouped survival data, i.e. occurrence/exposure data over given time intervals and covariate strata. We derive a Sheppard correction for the bias in the grouped data analogue of Cox's maximum partial likelihood estimator. This is done via a large sample theory in which the covariate strata and time intervals shrink as the sample size increases.

We fit a Cox proportional hazards (PH) model to interval-censored survival data by first subdividing each individual's failure interval into nonoverlapping sub-intervals. Using the set of all endpoints in set, those that fall are then used as cut points for Each sub-interval has an accompanying weight calculated from parametric Weibull based on current parameter estimates. A weighted PH is with...

conclusions the use of smoothing methods helps us to eliminate non-linear effects but it is more appropriate to use cox proportional hazards model in medical data because of its’ ease of interpretation and capability of modeling both continuous and discrete covariates. also, cox proportional hazards model and smoothing methods analysis identified that age at diagnosis and tumor size were indepe...