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
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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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Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent [PDF]
Journal of Statistical Software, 2011 We introduce a pathwise algorithm for the Cox proportional hazards model, regularized by convex combinations of l1 and l2 penalties (elastic net). Our algorithm fits via cyclical coordinate descent, and employs warm starts to find a solution along a ...
Noah Simon +3 more
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A novel 14-gene signature for overall survival in lung adenocarcinoma based on the Bayesian hierarchical Cox proportional hazards model [PDF]
Scientific Reports, 2022 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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Estimation of treatment effects in weighted log-rank tests
Contemporary Clinical Trials Communications, 2017 Non-proportional hazards have been observed in clinical trials. The log-rank test loses power and the standard Cox model generally produces biased estimates under such conditions.
Ray S. Lin, Larry F. León
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Efficient Estimation and Inference in the Proportional Odds Model for Survival Data
Mathematics, 2022 In modeling time-to-event data with long-term survivors, the proportional hazards model is widely used for its easy and direct interpretation as well as the flexibility to accommodate the past information and allow time-varying predictors.
Xifen Huang +4 more
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A flexible alternative to the Cox proportional hazards model for assessing the prognostic accuracy of hospice patient survival. [PDF]
PLoS ONE, 2012 Prognostic models are often used to estimate the length of patient survival. The Cox proportional hazards model has traditionally been applied to assess the accuracy of prognostic models.
Branko Miladinovic +5 more
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Frontiers in Medicine, 2022 BackgroundPrognostic models can help to identify patients at risk for end-stage kidney disease (ESKD) at an earlier stage to provide preventive medical interventions. Previous studies mostly applied the Cox proportional hazards model.
Xi Shi +6 more
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A semiparametric Bayesian proportional hazards model for interval censored data with frailty effects
BMC Medical Research Methodology, 2009 Background Multivariate analysis of interval censored event data based on classical likelihood methods is notoriously cumbersome. Likelihood inference for models which additionally include random effects are not available at all.
Hölzel Dieter +3 more
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Prognostic Factors in Patients With Colorectal Cancer at Hospital Universiti Sains Malaysia
Asian Journal of Surgery, 2010 To determine the 5-year survival rate and prognostic factors for survival in patients with colorectal cancer treated at the Surgical Unit, Hospital Universiti Sains Malaysia (HUSM), Kelantan, Malaysia.
Anis Kausar Ghazali +3 more
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