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Peak detection of the plasma cortisol time series by syntactic pattern recognition

机译:通过句法模式识别对血浆皮质醇时间序列进行峰值检测

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A syntactic peak recognition algorithm was applied to identify the significant peaks in the sampled profiles of cortisol concentration for 29 normal subjects and 49 patients with Cushing's syndrome. To estimate the parameters of the criterion for a significant peak, the random measurement error in the laboratory assay must first be established, and the first derivative of the cortisol time series must be calculated. This process is described. The syntatic peak recognition algorithm was applied to the time series to identify significant secretory peaks. The mean of the number of peaks in the normal group proved to be significantly different from the respective means of the number of peaks in the individual patient subgroups. This result may be useful in the diagnosis of Cushing's syndrome.
机译:应用句法峰识别算法来识别29名正常受试者和49位库欣综合征的皮质醇浓度的采样曲线中的显着峰。为了估计显着峰的标准参数,必须首先确定实验室分析中的随机测量误差,并且必须计算皮质醇时间序列的一阶导数。描述了该过程。将句法峰识别算法应用于时间序列以识别显着的分泌峰。正常组中峰数的平均值被证明与各个患者亚组中峰数的相应平均值有显着差异。该结果可能对库欣综合症的诊断有用。

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