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一种用于对含有随机比例异常细胞的标本进行分类的模型。

A model for the classification of specimens containing random proportions of abnormal cells.

作者信息

Timmers T, Gelsema E S

出版信息

Cytometry. 1985 Jan;6(1):22-5. doi: 10.1002/cyto.990060105.

Abstract

The effect of abnormal cell proportion on the performance of an automated cervical prescreening system is discussed in K.R. Castleman and B.S. White, Cytometry 2:155-18. The model employed assumes fixed proportions of abnormal cells, both in the design stage and in the test stage. In the present paper, an extended model is developed that allows for random variability of this proportion. It is shown, that there is a fundamental, non-zero lower limit to the false-negative specimen error rate, which depends only on the coefficient of variation. This limit may be reached even for moderate values of the coefficient of variation, which implies that a satisfactory prescreening system may not be feasible.

摘要

K.R. 卡斯尔曼和B.S. 怀特在《细胞计数》第2卷第155 - 158页中讨论了异常细胞比例对自动宫颈预筛查系统性能的影响。所采用的模型在设计阶段和测试阶段都假定异常细胞比例是固定的。在本文中,我们开发了一个扩展模型,该模型考虑了这一比例的随机变异性。结果表明,假阴性样本错误率存在一个基本的非零下限,该下限仅取决于变异系数。即使变异系数为中等值时也可能达到这个下限,这意味着一个令人满意的预筛查系统可能不可行。

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