Artificial Neural Networks in Medicine and Biology: by Pierre Baldi, Gianluca Pollastri, Claus A. F. Andersen,

By Pierre Baldi, Gianluca Pollastri, Claus A. F. Andersen, Søren Brunak (auth.), Helge Malmgren BA, PhD, MD, Magnus Borga MSc, PhD, Lars Niklasson BSc, MSc, PhD (eds.)

This ebook comprises the court cases of the convention ANNIMAB-l, held 13-16 could 2000 in Goteborg, Sweden. The convention was once prepared through the Society for man made Neural Networks in medication and Biology (ANNIMAB-S), which was once demonstrated to advertise learn inside a brand new and certainly cross-disciplinary box. Forty-two contributions have been authorised for presentation; as well as those, S invited papers also are incorporated. examine inside drugs and biology has frequently been characterized by way of software of statistical tools for comparing area particular information. The becoming curiosity in man made Neural Networks has not just brought new equipment for facts research, but additionally spread out for improvement of recent versions of organic and ecological structures. The ANNIMAB-l convention is concentrating on a few of the many makes use of of man-made neural networks with relevance for medication and biology, in particular: • clinical purposes of man-made neural networks: for larger diagnoses and final result predictions from medical and laboratory info, within the processing of ECG and EEG indications, in clinical photo research, and so forth. greater than half the contributions tackle such clinically orientated matters. • makes use of of ANNs in biology outdoor medical drugs: for instance, in versions of ecology and evolution, for info research in molecular biology, and (of direction) in versions of animal and human apprehensive structures and their features. • Theoretical features: contemporary advancements in studying algorithms, ANNs with regards to professional structures and to conventional statistical techniques, hybrid platforms and integrative approaches.

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Self-organizing formation of topologically correct feature maps. Biological Cybernetics, 43:59-69, 1982. [33) J. Hertz, A. G. Palmer. Introduction to the Theory of Neuml Computation. Addison-Wesley, Reading, MA, 1991. J. Lux, A. Stellzig, D. Volz, W. Jager, A. Richardson, and G. Komposch. A neural network approach to the analysis and classification of human craniofacial growth. Growth, Development, & Aging, 62(3):95-106, 1998. 1. S. Pattichis. Unsupervised pattern recognition for the classification of EMG signals.

36 [46] R Dybowski. Classification of incomplete feature vectors by radial basis function networks. Pattern Recognition Letters, 19:1257-1264, 1998. [47] LT. Nabney. Efficient training of RBF networks for classification. Technical report NCRG/99/002, Neural Computing Research Group, Aston University, 1999. A. Carpenter and S. Grossberg. A massively parallel architecture for a selforganizing neural pattern recognition machine. Computer Vision, Graphics, and Image Processing, 37:54-115, 1987. [49] M.

An example of how Bayesian inference can be used for estimating uncertainty is shown in Fig 3. An EEG signal is plotted, which is ·contaminated by muscle 4 SIESTA ("A New Standard for Integrating Polygraphic Sleep Recordings into a Comprehensive Model of Human Sleep and Its Validation in Sleep Disorders") is Biomed-2 project no. BMH4-CT97-2040, sponsored by the European Commission, DG XII. 24 artifacts, as they frequently occur during sleep when the person is moving. A common method for extracting features from the signal is the use of autoregressive models, estimated over a window of quasi-stationary signal.

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