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Potential of radial basis function neural networks in discriminating benign from malignant lesions of the lower urinary tract.

Authors
Type
Published Article
Journal
Analytical and quantitative cytology and histology / the International Academy of Cytology [and] American Society of Cytology
Publication Date
Volume
27
Issue
1
Pages
35–42
Identifiers
PMID: 15794450
Source
Medline
License
Unknown

Abstract

The role of nuclear morphologic features in the cytologic diagnosis of lower urinary tract alterations was confirmed by the results of this study. The observed overlap in feature space indicates that the nuclear characteristics do not form strictly separate clusters; that fact explains the difficulty morphologists have with reproducible identification of nuclei from the lower urinary tract. Application of RBF offers good classification at the nuclear and patient level and promises to become a powerful tool for everyday practice in the cytologic laboratory.

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