Limitations of using COX proportional hazards model in cardiovascular research [PDF]
Cardiovascular DiabetologyThe article by Zhao et al. titled “Associations of Triglyceride-Glucose (TyG) Index with Chest Pain Incidence and Mortality among the U.S. Population” provides valuable insights into the positive correlation between the TyG index and chest pain incidence,
Nan Jiang, Yongfa Wu, Chengjia Li
doaj +4 more sources
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,
I. Sohn +3 more
semanticscholar +6 more sources
Limitations of applying the COX proportional hazards model to glioma studies [PDF]
Journal of Translational MedicineJihao Xue +6 more
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On model specification and selection of the Cox proportional hazards model. [PDF]
Stat Med, 2013 Prognosis plays a pivotal role in patient management and trial design. A useful prognostic model should correctly identify important risk factors and estimate their effects. In this article, we discuss several challenges in selecting prognostic factors and estimating their effects using the Cox proportional hazards model.
Lin CY, Halabi S.
europepmc +6 more sources
Verticox+: vertically distributed Cox proportional hazards model with improved privacy guarantees [PDF]
Complex & Intelligent SystemsFederated learning allows us to run machine learning algorithms on decentralized data when data sharing is not permitted due to privacy concerns. Various models have been adapted to use in a federated setting.
Florian van Daalen +4 more
doaj +2 more sources
Accurate training of the Cox proportional hazards model on vertically-partitioned data while preserving privacy [PDF]
BMC Medical Informatics and Decision Making, 2022 Background Analysing distributed medical data is challenging because of data sensitivity and various regulations to access and combine data. Some privacy-preserving methods are known for analyzing horizontally-partitioned data, where different ...
Bart Kamphorst +4 more
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Data generation for the Cox proportional hazards model with time-dependent covariates: A method for medical researchers [PDF]
Statistics in Medicine, 2013 The proliferation of longitudinal studies has increased the importance of statistical methods for time-to-event data that can incorporate time-dependent covariates. The Cox proportional hazards model is one such method that is widely used.
Hendry, David J.
core +2 more sources
Cox proportional hazards model with Bayesian neural network for survival prediction [PDF]
Scientific ReportsSurvival analysis plays a crucial aspect in medical research and other domains where understanding the time-to-events is paramount. In this study, we present a novel approach for estimating survival outcomes that combines Bayesian neural networks with ...
Fojan Faghiri, Akram Kohansal
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Relaxing the independent censoring assumption in the Cox proportional hazards model using multiple imputation. [PDF]
Stat Med, 2014 The Cox proportional hazards model is frequently used in medical statistics. The standard methods for fitting this model rely on the assumption of independent censoring.
Jackson D +5 more
europepmc +2 more sources
Reasons why osteoarthritis predicts mortality: path analysis within a Cox proportional hazards model [PDF]
RMD Open, 2019 Objectives To identify potentially modifiable factors that mediate the association between symptomatic osteoarthritis (OA) and premature mortality.Methods A population-based prospective cohort study; primary care medical record data were linked to self ...
George Peat +7 more
doaj +2 more sources