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SHR Neuro Krebs Kardio Lipid Stoffw Microb

Leistritz, L; Galicki, M; Kochs, E; Zwick, EB; Fitzek, C; Reichenbach, JR; Witte, H.
Application of generalized dynamic neural networks to biomedical data.
IEEE Trans Biomed Eng. 2006; 53(11):2289-2299 Doi: 10.1109/TBME.2006.881766
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Co-Autor*innen der Med Uni Graz
Zwick Bernhard-Ernst

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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.
Find related publications in this database (using NLM MeSH Indexing)
Algorithms -
Biomedical Engineering - methods
Databases, Factual - methods
Diagnosis, Computer-Assisted - methods
Information Storage and Retrieval - methods
Neural Networks (Computer) - methods
Pattern Recognition, Automated - methods
Signal Processing, Computer-Assisted - methods

Find related publications in this database (Keywords)
classification of temporal sequences
dynamic neural networks (DNNs)
optimal control
pattern recognition
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