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非典型尿路上皮细胞的计算机分析。I. 基于监督学习算法的分类

Computer analysis of atypical urothelial cells. I. Classification by supervised learning algorithms.

作者信息

Koss L G, Bartels P H, Bibbo M, Freed S Z, Sychra J J, Taylor J, Wied G L

出版信息

Acta Cytol. 1977 Mar-Apr;21(2):247-60.

PMID:324216
Abstract

Computer discrimination of atypical (ATY) urothelial cells from the urinary sediment by means of supervised learning algorithms discoled that these cells form a distinct, although ill-defined, family of cells which differs from normal (NEG) and malignant (POS) cell groups. The clinical significance of this observation must await long-term clinical follow-up. The possibility of issuing computer displays on individual patients with possible diagnostic and prognostic implications is discussed.

摘要

通过监督学习算法对尿沉渣中的非典型(ATY)尿路上皮细胞进行计算机识别发现,这些细胞形成了一个独特的细胞家族,尽管其定义尚不明确,且与正常(NEG)和恶性(POS)细胞群体不同。这一观察结果的临床意义尚需长期临床随访。本文还讨论了针对个体患者出具具有可能的诊断和预后意义的计算机显示结果的可能性。

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