Limitations of using COX proportional hazards model in cardiovascular research [PDF]
The 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 +3 more sources
Combining symbolic regression with the Cox proportional hazards model improves prediction of heart failure deaths [PDF]
Background Heart failure is a clinical syndrome characterised by a reduced ability of the heart to pump blood. Patients with heart failure have a high mortality rate, and physicians need reliable prognostic predictions to make informed decisions about ...
Casper Wilstrup, Chris Cave
doaj +3 more sources
A novel 14-gene signature for overall survival in lung adenocarcinoma based on the Bayesian hierarchical Cox proportional hazards model [PDF]
There have been few investigations of cancer prognosis models based on Bayesian hierarchical models. In this study, we used a novel Bayesian method to screen mRNAs and estimate the effects of mRNAs on the prognosis of patients with lung adenocarcinoma ...
Na Sun +5 more
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Moving beyond the Cox proportional hazards model in survival data analysis: a cervical cancer study [PDF]
Objectives This study explored the prognostic factors and developed a prediction model for Chinese-American (CA) cervical cancer (CC) patients. We compared two alternative models (the restricted mean survival time (RMST) model and the proportional ...
Lixian Li +3 more
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Verticox+: vertically distributed Cox proportional hazards model with improved privacy guarantees [PDF]
Federated 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
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On Cox proportional hazards model performance under different sampling schemes. [PDF]
Cox's proportional hazards model (PH) is an acceptable model for survival data analysis. This work investigates PH models' performance under different efficient sampling schemes for analyzing time to event data (survival data). We will compare a modified
Hani Samawi, Lili Yu, JingJing Yin
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VERTICOX: Vertically Distributed Cox Proportional Hazards Model Using the Alternating Direction Method of Multipliers. [PDF]
The Cox proportional hazards model is a popular semi-parametric model for survival analysis. In this paper, we aim at developing a federated algorithm for the Cox proportional hazards model over vertically partitioned data (i.e., data from the same ...
Dai W +5 more
europepmc +2 more sources
Quasi-linear Cox proportional hazards model with cross- L1 penalty [PDF]
Background To accurately predict the response to treatment, we need a stable and effective risk score that can be calculated from patient characteristics.
Katsuhiro Omae, Shinto Eguchi
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The Impact of Violation of the Proportional Hazards Assumption on the Calibration of the Cox Proportional Hazards Model [PDF]
INTRODUCTION The Cox proportional hazards regression model is frequently used to develop clinical prediction models for time-to-event outcomes, allowing clinicians to estimate an individual’s risk of experiencing the outcome within specified time ...
Peter Austin, Daniele Giardiello
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Adjusting for bias introduced by instrumental variable estimation in the Cox Proportional Hazards Model [PDF]
Instrumental variable (IV) methods are widely used for estimating average treatment effects in the presence of unmeasured confounders. However, the capability of existing IV procedures, and most notably the two-stage residual inclusion (2SRI) procedure ...
Goodney, Philip P. +4 more
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