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A step-by-step algorithm for combining diagnostic tests

机译:组合诊断测试的分步算法

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摘要

Combining data of several tests or markers for the classification of patients according to their health status for assigning better treatments is a major issue in the study of diseases such as cancer. In order to tackle this problem, several approaches have been proposed in the literature. In this paper, a step-by-step algorithm for estimating the parameters of a linear classifier that combines several measures is considered. The optimization criterion is to maximize the area under the receiver operating characteristic curve. The algorithm is applied to different simulated data sets and its performance is evaluated. Finally, the method is illustrated with a prostate cancer staging database.
机译:结合几种测试或标记物的数据以根据患者的健康状况对患者进行分类以分配更好的治疗方法是研究癌症等疾病的主要问题。为了解决这个问题,文献中已经提出了几种方法。在本文中,考虑了一种估计线性分类器参数的分步算法,该算法结合了多种措施。优化标准是使接收器工作特性曲线下的面积最大化。该算法被应用于不同的模拟数据集,并对其性能进行了评估。最后,用前列腺癌分期数据库说明了该方法。

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