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A Federated Cox Model with Non-Proportional Hazards
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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Estimation in a Cox Proportional Hazards Cure Model [PDF]
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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Gradient lasso for Cox proportional hazards model [PDF]
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]
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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Numerous methods and approaches have been developed for generating time-to-event data from the Cox Proportional Hazards (CPH) model; however, they often require specification of a parametric distribution for the baseline hazard even though the CPH model ...
Jennifer L. Delzeit, Devin C. Koestler
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Comparison of radiomic feature aggregation methods for patients with multiple tumors
Radiomic feature analysis has been shown to be effective at analyzing diagnostic images to model cancer outcomes. It has not yet been established how to best combine radiomic features in cancer patients with multifocal tumors.
Enoch Chang +7 more
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Background Uganda just like any other Sub-Saharan African country, has a high under-five child mortality rate. To inform policy on intervention strategies, sound statistical methods are required to critically identify factors strongly associated with ...
Justine B. Nasejje, Henry Mwambi
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Testing proportional hazards for specified covariates
Tests for proportional hazards assumption concerning specified covariates or groups of covariates are proposed. The class of alternatives is wide: log-hazard rates under different values of covariates may cross, approach, go away.
Vilijandas Bagdonavičius +1 more
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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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Survival analysis is a statistical method that accommodates the collection of censored data. One of popular method in survival analysis is the Cox Proportional Hazard Regression.
I GEDE ARI SUDANA +2 more
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