Automated Disease Classification in Cytometry

The development of disease classifiers is of high interest for the standardized and automated information extraction from multiparameter flow cytometric list mode and other (e.g. clinical chemistry) data.

Various statistical, cluster analysis, neural network, expert system, triple matrix, principal component, expert system and fuzzy logic classifiers have been proposed for cytometric data classification.

It is the intention of this forum to shortly discuss the concepts of various classification methods, to comparatively classify list mode data sets of diseased patients and normal individuals and to display the respective results.

  • Cytorelay

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    For problems or comments, please contact:
    G.Valet, E-mail: valet@vms.biochem.mpg.de , Max-Planck-Institut für Biochemie, Am Klopferspitz 18a, D-82152 Martinsried, Germany, Tel: +49/89/8578-2518, -2525, Fax: +49/89/8578-2563, INTERNET address: http://www.biochem.mpg.de/valet/cytorel.html
    Last update: Aug.28, 1996
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    CD ROM Vol 2 was produced by staff at the Purdue University Cytometry Laboratories and distributed free of charge as an educational service to the cytometry community. If you have any comments please direct them to Dr. J. Paul Robinson, Professor & Director, PUCL, Purdue University, West Lafayette, IN 47907. Phone:(317) 494-0757; FAX (317) 494-0517; Web http://www.cyto.purdue.edu EMAIL robinson@flowcyt.cyto.purdue.edu