Results 11 to 20 of about 14,848,273 (189)
Cancer Informatics, 2011 In the frame of the Cox proportional hazard (PH) model, a novel two-step procedure for estimating age-period-cohort (APC) effects on the hazard function of death from cancer was developed. In the first step, the procedure estimates the influence of joint
Tengiz Mdzinarishvili +3 more
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Generating Survival Times to Simulate Cox Proportional Hazards Models [PDF]
Statistics in Medicine, 2003 This paper discusses techniques to generate survival times for simulation studies regarding Cox proportional hazards models. In linear regression models, the response variable is directly connected with the considered covariates, the regression ...
Blettner, Maria +3 more
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Diagnostic and Prognostic ResearchBackground The Cox proportional hazards regression model is frequently used to estimate an individual’s probability of experiencing an outcome within a specified prediction horizon. A key assumption of this model is that of proportional hazards.
Peter C. Austin, Daniele Giardiello
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Estimation in a Cox Proportional Hazards Cure Model [PDF]
Biometrics, 2000 Summary.Some failure time data come from a population that consists of some subjects who are susceptible to and others who are nonsusceptible to the event of interest. The data typically have heavy censoring at the end of the follow‐up period, and a standard survival analysis would not always be appropriate.
Sy, Judy P., Taylor, Jeremy M. G.
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A Federated Cox Model with Non-Proportional Hazards
CoRR, 2022 Recent research has shown the potential for neural networks to improve upon classical survival models such as the Cox model, which is widely used in clinical practice. Neural networks, however, typically rely on data that are centrally available, whereas healthcare data are frequently held in secure silos.
Dekai Zhang +2 more
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Clinical and Translational Science, 2022 This study aimed to develop a model for predicting the completion of clinical trials involving pregnant women using the Cox proportional hazard model and neural network model (DeepSurv) and to compare the predictive performance of both methods.
Bomee Kim +6 more
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Gradient lasso for Cox proportional hazards model [PDF]
Bioinformatics, 2009 AbstractMotivation: There has been an increasing interest in expressing a survival phenotype (e.g. time to cancer recurrence or death) or its distribution in terms of a subset of the expression data of a subset of genes. Due to high dimensionality of gene expression data, however, there is a serious problem of collinearity in fitting a prediction model,
Insuk Sohn +3 more
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Tree-augmented Cox proportional hazards models [PDF]
Biostatistics, 2005 We study a hybrid model that combines Cox proportional hazards regression with tree-structured modeling. The main idea is to use step functions, provided by a tree structure, to 'augment' Cox (1972) proportional hazards models. The proposed model not only provides a natural assessment of the adequacy of the Cox proportional hazards model but also ...
Su, Xiaogang, Tsai, Chih Ling
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BMC Bioinformatics, 2021 Background The Cox proportional hazards model is commonly used to predict hazard ratio, which is the risk or probability of occurrence of an event of interest.
Eu-Tteum Baek +6 more
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A mixed model approach for structured hazard regression [PDF]
, 2004 The classical Cox proportional hazards model is a benchmark approach to analyze continuous survival times in the presence of covariate information. In a number of applications, there is a need to relax one or more of its inherent assumptions, such as ...
Thomas Kneib +4 more
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