TY - JOUR
T1 - Application of generalized dynamic neural networks to biomedical data
AU - Leistritz, Lutz
AU - Galicki, Miroslaw
AU - Kochs, Eberhard
AU - Zwick, Ernst Bernhard
AU - Fitzek, Clemens
AU - Reichenbach, Jürgen R.
AU - Witte, Herbert
PY - 2006/11
Y1 - 2006/11
N2 - This paper reviews the application of continuous recurrent neural networks with time-varying weights to pattern recognition tasks in medicine. A general learning algorithm based on Pontryagin's maximum principle is recapitulated, and possibilities of improving the generalization capabilities of these networks are given. The effectiveness of the methods is demonstrated by three different real-world examples taken from the fields of anesthesiology, orthopedics, and radiology.
AB - This paper reviews the application of continuous recurrent neural networks with time-varying weights to pattern recognition tasks in medicine. A general learning algorithm based on Pontryagin's maximum principle is recapitulated, and possibilities of improving the generalization capabilities of these networks are given. The effectiveness of the methods is demonstrated by three different real-world examples taken from the fields of anesthesiology, orthopedics, and radiology.
KW - Classification of temporal sequences
KW - Dynamic neural networks (DNNs)
KW - Optimal control
KW - Pattern recognition
UR - http://www.scopus.com/inward/record.url?scp=33750333533&partnerID=8YFLogxK
U2 - 10.1109/TBME.2006.881766
DO - 10.1109/TBME.2006.881766
M3 - Article
C2 - 17073335
AN - SCOPUS:33750333533
SN - 0018-9294
VL - 53
SP - 2289
EP - 2299
JO - IEEE Transactions on Biomedical Engineering
JF - IEEE Transactions on Biomedical Engineering
IS - 11
ER -