[计算机辅助筛查方法(PAPNET)在检测感染性宫颈子宫涂片中的价值]。

M Bernier, A M Bergemer, C Got, C Marsan
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引用次数: 0

摘要

关于PAPNET系统用于癌症和癌前病变筛查的准确性,已有几篇报道。基于神经网络,这个计算机化工具最初被训练来选择非典型细胞。它已获美国批准用于子宫颈细胞检验的再筛查,以保证质量。然而,当该系统被设计用于检测常见的传染性生物体时,其特殊行为并未经常被研究。我们报告用PAPNET系统重新筛查42例宫颈-子宫炎症涂片的结果。计算机图像由两位不同的病理学家审查,在39例中,两位观察者完全一致。仅在66%的病例中检测到传染性微生物。滴虫病、霉菌病和加德纳菌的诊断率分别为63%、56%和87%。未发现疱疹性病变。如果将PAPNET系统作为一种独家的预筛查方法开发,则应考虑到PAPNET系统在感染性宫颈子宫涂片诊断中的低准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Value of a computer-assisted screening method (PAPNET) for the detection of infectious cervico-uterine smears].

There have been several reports regarding the accuracy of the PAPNET system applied to the screening for cancerous and precancerous lesions. Based on neuronal networks, this computerized tool was initially trained to select atypical cells. It has been approved in the USA for the re-screening of cervical smears for quality assurance. However, its particular behaviour has not been frequently studied when the system is designed to detect frequent infectious organisms. We report the results of re-screening of 42 inflammatory cervico-uterine smears by the PAPNET system. The computerized images were reviewed by two different pathologists, with complete agreement between the two observers in 39 cases. Infectious organisms were detected in only 66% of cases. Trichomonas, mycoses and Gardnerella were diagnosed in 63%, 56% and 87% of cases respectively. No herpetic lesions were identified. The low accuracy of the PAPNET system in the diagnosis of infectious cervico-uterine smears should be taken into account if this system is developed as an exclusive pre-screening method.

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