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Published in 2019 at "Statistics in medicine"
DOI: 10.1002/sim.8090
Abstract: Some interesting recent studies have shown that neural network models are useful alternatives in modeling survival data when the assumptions of a classical parametric or semiparametric survival model such as the Cox (1972) model are…
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Keywords:
cox model;
extreme learning;
learning machine;
model ... See more keywords
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Published in 2023 at "Statistics in medicine"
DOI: 10.1002/sim.9760
Abstract: The Cox regression, a semi-parametric method of survival analysis, is extremely popular in biomedical applications. The proportional hazards assumption is a key requirement in the Cox model. To accommodate non-proportional hazards, we propose to parameterize…
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Keywords:
proportional hazards;
cox;
double cox;
cox model ... See more keywords
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Published in 2019 at "Journal of Applied Statistics"
DOI: 10.1080/02664763.2019.1681946
Abstract: Including time-varying covariates is a popular extension to the Cox model and a suitable approach for dealing with non-proportional hazards. However, partial likelihood (PL) estimation of this model has three shortcomings: (i) estimated regression coefficients…
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Keywords:
baseline hazard;
time varying;
cox model;
time ... See more keywords
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Published in 2023 at "Journal of biopharmaceutical statistics"
DOI: 10.1080/10543406.2023.2170393
Abstract: Many clinical trials include time-to-event or survival data as an outcome. To compare two survival distributions, the log-rank test is often used to produce a P-value for a statistical test of the null hypothesis that…
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Keywords:
win ratio;
test;
cox model;
treatment ... See more keywords
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Published in 2020 at "Archives of Suicide Research"
DOI: 10.1080/13811118.2020.1735596
Abstract: Abstract Aim Brief contact interventions (such as letters, green cards, telephone calls or postcards) for reducing suicide reattempt (SR) and suicide have been evaluated since the 1980s, but results have been inconsistent. VigilanS is one…
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Keywords:
nonexposed patients;
cox model;
program;
propensity score ... See more keywords
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Published in 2021 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btaa1046
Abstract: MOTIVATION Accurately predicting the risk of cancer patients is a central challenge for clinical cancer research. For high-dimensional gene expression data, Cox proportional hazard model with the least absolute shrinkage and selection operator for variable…
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Keywords:
cox model;
model;
lasso cox;
gene interaction ... See more keywords
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Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2022.3218585
Abstract: To exploit large-scale biomedical data, the application of common data models and the establishment of data networks are being actively carried out worldwide. However, due to the privacy issues, it is difficult to share data…
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Keywords:
time;
data distributed;
wicox;
cox model ... See more keywords
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Published in 2017 at "Frontiers in Human Neuroscience"
DOI: 10.3389/fnhum.2017.00033
Abstract: Mild cognitive impairment (MCI) represents a transitional stage from normal aging to Alzheimer’s disease (AD) and corresponds to a higher risk of developing AD. Thus, it is necessary to explore and predict the onset of…
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Keywords:
combination;
network;
cox model;
analysis ... See more keywords
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Published in 2022 at "Acta Informatica Medica"
DOI: 10.5455/aim.2022.30.295-301
Abstract: Background: COVID-19 pandemic has created many challenges for clinicians. The monitoring trend for laboratory biomarkers is helpful to provide additional information to determine the role of those in the severity status and death outcome. Objective:…
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Keywords:
varying biomarkers;
time;
extended cox;
cox model ... See more keywords