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 includes the court cases of the convention ANNIMAB-l, held 13-16 may perhaps 2000 in Goteborg, Sweden. The convention used to be equipped through the Society for synthetic Neural Networks in medication and Biology (ANNIMAB-S), which used to be proven to advertise examine inside a brand new and certainly cross-disciplinary box. Forty-two contributions have been accredited for presentation; as well as those, S invited papers also are incorporated. study inside medication and biology has usually been characterized by means of software of statistical tools for comparing area particular facts. The transforming into curiosity in synthetic Neural Networks has not just brought new equipment for information research, but additionally spread out for improvement of recent versions of organic and ecological platforms. The ANNIMAB-l convention is targeting a few of the many makes use of of synthetic neural networks with relevance for medication and biology, in particular: • scientific functions 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 deal with such clinically orientated matters. • makes use of of ANNs in biology outdoors scientific medication: for instance, in versions of ecology and evolution, for info research in molecular biology, and (of direction) in types of animal and human fearful platforms and their services. • Theoretical points: contemporary advancements in studying algorithms, ANNs with regards to professional structures and to conventional statistical techniques, hybrid structures and integrative approaches.

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The design of ANNs was originally motivated by the phenomena of learning and recognition, and the desire to model these cognitive processes. The cognitive-modelling branch of ANN research is still active, and it is relevant to medicine in providing models of psychological and cerebral dysfunction [1, 2, 3). However, in the late 1980s, a more pragmatic stance emerged, and ANNs became to be seen also as tools for data modelling, primarily for classification. Medicine involves decision making, and classification is an integral part of that process, but medical classification tasks, such as diagnosis, can be far from straightforward.

Titterington. Neural networks: A review from a statistical perspective. Statistical Science, 9:2-54, 1994. D. M. Ripley. Neural networks as statistical methods in survival analysis. In R. Dybowski and V. Gant, editors, Clinical Applications of Artificial Neural Networks, chapter 9. Cambridge University Press, Cambridge. In press. D. Ripley. Pattern Recognition and Neural Networks. Cambridge University Press, Cambridge, 1996. [23] S. Haykin. Neural Networks: A Comprehensive Foundation. Macmillan, New York,1994.

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