This project is an exploration of the performance of parametric and nonparametric methods in predicting time to recurrence (progression of cancer) and time to death in late stage ovarian cancer patients. The Weibull survival model is a common parametric method and is fit to the data for both death and recurrence, while Ishwaran et al’s method of fitting random survival forests (2008) is employed as a nonparametric method. Performance of these models is evaluated using Harrell’s C-index and Lawless & Yuan’s cross-validation estimator (2010)
The objective of the present study is to investigate key aspects of ovarian and breast cancers, ...
AimTo establish prediction models for 2-year overall survival of ovarian cancer patients with metast...
In this study we used the parametric survival approach to analyze the survival time of African Ameri...
Survival time predictions have far-reaching implications. For example, such predictions can be infl...
Predicting survival time has many Effective implications in life quality management for the remainde...
Predicting survival time has many Effective implications in life quality management for the remainde...
In this paper, we propose a suitable statistical model for survival time of the ovarian cancer patie...
In this paper, we propose a suitable statistical model for survival time of the ovarian cancer patie...
Survival analysis involves the study of time until an event of interest occurs, or lifetimes. This a...
Aim: The aim of this study is to determine the factors influencing predicted survival time for patie...
Ovarian cancer is one of the most deadly women's gynecological malignancies in the world, and despit...
BACKGROUND: Ovarian cancer is the fifth leading cause of mortality among women in the United States....
Abstract Background: Colorectal cancer is the most common gastrointestinal cancer. Investigating th...
Abstract Background Ovarian cancer is the fifth leading cause of mortality among women in the United...
The objective of the present study is to investigate key aspects of ovarian and breast cancers, ...
The objective of the present study is to investigate key aspects of ovarian and breast cancers, ...
AimTo establish prediction models for 2-year overall survival of ovarian cancer patients with metast...
In this study we used the parametric survival approach to analyze the survival time of African Ameri...
Survival time predictions have far-reaching implications. For example, such predictions can be infl...
Predicting survival time has many Effective implications in life quality management for the remainde...
Predicting survival time has many Effective implications in life quality management for the remainde...
In this paper, we propose a suitable statistical model for survival time of the ovarian cancer patie...
In this paper, we propose a suitable statistical model for survival time of the ovarian cancer patie...
Survival analysis involves the study of time until an event of interest occurs, or lifetimes. This a...
Aim: The aim of this study is to determine the factors influencing predicted survival time for patie...
Ovarian cancer is one of the most deadly women's gynecological malignancies in the world, and despit...
BACKGROUND: Ovarian cancer is the fifth leading cause of mortality among women in the United States....
Abstract Background: Colorectal cancer is the most common gastrointestinal cancer. Investigating th...
Abstract Background Ovarian cancer is the fifth leading cause of mortality among women in the United...
The objective of the present study is to investigate key aspects of ovarian and breast cancers, ...
The objective of the present study is to investigate key aspects of ovarian and breast cancers, ...
AimTo establish prediction models for 2-year overall survival of ovarian cancer patients with metast...
In this study we used the parametric survival approach to analyze the survival time of African Ameri...