نتایج جستجو برای: survival models
تعداد نتایج: 1214086 فیلتر نتایج به سال:
Background: Kidney transplantation had been evaluated in some researches in Iran mainly with clinical approach. In this research we evaluated graft survival in kidney recipients and factors impacting on survival rate. Artificial neural networks have a good ability in modeling complex relationships, so we used this ability to demonstrate a model for prediction of 5yr graft survival after ki...
Nowadays, one of the most important topics in risk management of banks, financial, and credit institutions is credit risk management. In this research, the researchers used survival analytic methods for credit risk modeling in terms of the conditional distribution function of default time. As a practical task, the authors considered the reward credit portfolio of Tose'e Ta'avon Bank of Guilan P...
conclusions herein we have described the stata package “adpredsurv” for calculation of the nam-d’agostino x2 goodness of fit test as well as cut point-free and cut point-based nri, relative and absolute idi, and survival-based regression analyses. we hope this work encourages the use of novel methods in examining predictive capacity of the emerging plethora of novel biomarkers. background a fun...
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...
The proportional hazard Cox regression models play a key role in analyzing censored survival data. We use penalized methods in high dimensional scenarios to achieve more efficient models. This article reviews the penalized Cox regression for some frequently used penalty functions. Analysis of medical data namely ”mgus2” confirms the penalized Cox regression performs better than the cox regressi...
background: precise diagnosis of disease risk factors via efficient statistical models is the primary step for reducing the heavy costs of breast cancer, as one of the most highly prevalent cancer throughout the world. therefore, the aim of this study was to present a recently introduced statistical model in order to assess its proficiency for model fitting. methods: the information of 1465 eli...
In industry or nature, there are systems subjected to a secuence of shocks ocurring randomly in time. these shocks are causing aging or failure of system. According to the type of shocks, shock models divided in two major groups, Extreme Shock Models and Cumulative Shock Models. In the extreme shock models just impact of last shock named fatal shock would be studied and in the cumul...
nowadays in trade and economic issues, prediction is proposed as the most important branch of science. existence of effective variables, caused various sectors of the economic and business executives to prefer having mechanisms which can be used in their decisions. in recent years, several advances have led to various challenges in the science of forecasting. economical managers in various fi...
BACKGROUND We present survival outcomes of patients registered in the Dutch population-based Eindhoven Cancer Registry (ECR). PATIENTS AND METHODS Data on patients diagnosed with a melanoma between 1980 and 2002 were obtained from the ECR. Data on vital status up to 1 January 2005 were obtained, up-to-date survival rates were calculated using period analysis. Multivariate analyses were carrie...
background and objectives: survival models are statistical technique to estimate or predict the overall time up to specific events. prediction is important in medical science and the accuracy of prediction is determined by a measurement, generally based on loss functions, called prediction error. the aim of this study is using parametric models to determine the factors influencing predicted sur...
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