title: Classification of gynecologic flow cytometry data: a comparison of methods.
abstract: Several discriminant function methods for automatically classifying flow cytometry data from human cervical material were developed and compared with previously published methods using a sample of 186 specimens. The misclassification rates (approximately 20%) were similar to those of other published techniques for classifying these data. The methods misclassify different cases, however. The apparent system performance appears to be limited by at least three factors: (1) use of too small a sample in constructing classification algorithms, (2) poor "visibility" of small numbers of abnormal cells in the flow histograms and (3) incorrect or inconsistent visual classification of the samples used to construct the classification algorithms. The third factor results in erroneously high estimates of the misclassification rate. Even so, the overall system performance appears to be comparable to that of many cytotechnologists.
mesh_terms: D002584:Cervix Uteri / Q000166:cytology*; D003201:Computers; D003581:Cytodiagnosis / Q000379:methods*; D003584:Cytological Techniques; D005260:Female; D006801:Humans; D008433:Mathematics; D013050:Spectrometry, Fluorescence