Access the full text.
Sign up today, get DeepDyve free for 14 days.
J. Quinlan (1992)
C4.5: Programs for Machine Learning
L. Breiman, J. Friedman, R. Olshen, C. Stone (1984)
Classification and Regression TreesBiometrics, 40
P. Bartels (1980)
Numerical evaluation of cytologic data. IV. Discrimination and classification.Analytical and quantitative cytology, 2 1
CC Stewart, Z Darzynkiewicz (1990)
Methods in Cell Biology, 33
C. Stewart (1990)
Cell preparation for the identification of leukocytes.Methods in cell biology, 33
GC Salzman, JD Parson, RJ Beckman (1993)
AutoGate: A Macintosh cluster analysis program for flow cytometry. Abstract: XVI Congress of the International Society for Analytical Cytology, Colorado Springs, CO, March 20–26, 1993, 6
J. Morgan, J. Sonquist (1963)
Problems in the Analysis of Survey Data, and a ProposalJournal of the American Statistical Association, 58
F. Genter, G. Salzman (1979)
A statistical approach to the classification of biological cells from their diffraction patterns.The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society, 27
M. Bigos, D. Parks, W. Moore, L. Herzenberg (1994)
Pattern sorting: a computer-controlled multidimensional sorting method using k-d trees.Cytometry, 16 4
J. Nelder, R. Mead (1965)
A Simplex Method for Function MinimizationComput. J., 7
GC Salzman, SJ Stewart, CC Stewart (1994)
Normalization of clinical immunophenotyping data. Abstract: XVII Congress of the International Society for Analytical Cytology, Lake Placid, NY, October 16–21, 1994, 7
Methods are needed to assist with automating three‐color flow cytometric immunophenotyping of bone marrow from leukemia patients. Described is a method in which a normal bone marrow data set is used as a template against which to compare leukemic bone marrow data sets. This template is obtained using techniques of cluster analysis and cluster editing. Leukemic cells often inappropriately express antigens and appear in a different part of the multivariate data space than normal cells. To recognize the cells exhibiting inappropriate antigen expression, an artificial cluster of “cells” is added to the normal template. The “cells” in this cluster fill the space not occupied by normal cells. Classification and regression tree (CART) analysis is used to train a classifier that can then be used to isolate the major cell types and the inappropriate expression cells in a leukemic bone marrow specimen. © 1995 Wiley‐Liss, Inc.
Cytometry Part A – Wiley
Published: Jan 1, 1995
Keywords: ; ; ;
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.