Self-organizing neural networks - An alternative way of cluster analysis in clinical chemistry

Clinica Chimica Acta

Volumn 248, Issue 1, 1996, Pages 91-98

  Reibnegger, Gilbert ^a,c   Wachter, Helmut ^b  

^a UNIVERSITY OF GRAZ   (Austria)

^b UNIVERSITY OF INNSBRUCK   (Austria)

^c Inst für Medizinische Chemie   (Austria)

Author keywords

cluster analysis; connectionist models; neural networks; self organizing learning schemes; unsupervised learning schemes

Indexed keywords

ANALYTICAL ERROR; COMPUTER NETWORK; CONFERENCE PAPER; CONTROLLED STUDY; EDUCATION; INFORMATION PROCESSING; MILK; MODEL; NONHUMAN; PRIORITY JOURNAL; SPECIES DIFFERENCE; STATISTICS;

EID: 0029868682     PISSN: 00098981     EISSN: None     Source Type: Journal    
DOI: 10.1016/0009-8981(95)06269-6     Document Type: Conference Paper

References (7)

1. Rumelhard DE, Hinton GE, Williams RJ. Learning internal representations by error propagation. In: Rumelhard DE, McClelland JL, eds. Parallel distributed processing: exploration in the microstructure of cognition. Cambridge, MA: MIT Press, 1986;318-364.
2. Hartigan JA. Clustering algorithms. New York: Wiley, 1975.
3. Kohonen T. Self-organization and associative memory. Berlin: Springer, 1984.
4. Reibnegger G, Weiss G, Wachter H. Self-organizing neural networks as a means of cluster analysis in clinical chemistry. Eur J Clin Chem Clin Biochem 1993;31:311-316.
5. Livingstone DJ, Hesketh G, Clayworth D. Novel method for the display of multivariate data using neural networks. J Mol Graphics 1991;9:115-118.
6. Reibnegger G, Werner-Felmayer G, Wachter H. A note on the low-dimensional display of multivariate data using neural networks. J Mol Graphics 1993;11:129-133.
7. Baldi P, Hornik K. Neural networks and principal component analysis. Neural Networks 1989;2:53-58.