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Bayesian Assessment Of Times To Diagnosis In Breast Cancer Screening

机译:贝叶斯评估诊断乳腺癌的时间

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Breast cancer is one of the diseases with the most profound impact on health in developed countries and mammography is the most popular method for detecting breast cancer at a very early stage. This paper focuses on the waiting period from a positive mammogram until a confirmatory diagnosis is carried out in hospital. Generalized linear mixed models are used to perform the statistical analysis, always within the Bayesian reasoning. Markov chain Monte Carlo algorithms are applied for estimation by simulating the posterior distribution of the parameters and hyperparameters of the model through the free software WinBUGS.
机译:在发达国家,乳腺癌是对健康影响最深的疾病之一,而乳腺X射线照相术是在早期发现乳腺癌的最流行方法。本文重点介绍从乳房X线检查阳性到医院确定性诊断的等待期。始终在贝叶斯推理中使用广义线性混合模型执行统计分析。通过免费软件WinBUGS模拟模型的参数和超参数的后验分布,将马尔可夫链蒙特卡罗算法用于估计。

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