Titlebook: Artificial Neural Networks in Biomedicine; Paulo J. G. Lisboa,Emmanuel C. Ifeachor,Piotr S. S Book 2000 Springer-Verlag London 2000 Elektr

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The Application of PAPNET to Diagnostic Cytologyoscopic examination of cell samples, rather than tissue biopsies [1],[2]. There are several methods of obtaining cell samples. The cells may be secured by scraping or brushing the surface of the target organs (such as the uterine cervix, the oesophagus or the bronchus, to name a few). Cells may also

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Benchmark of Approaches to Sequential Diagnosis. Such a task, henceforth called the ., involves dealing with a complex decision problem. This is caused by the dependence of the patient’s state at a given time on the preceding states and on the already applied treatment. Although there remains no doubt as to the very existence of this dependence,

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Independent Components Analysise theoretical basis of ICA, outline an approach to non-stationary ICA, and describe a number of biomedical case studies. ICA is discussed in the framework of general linear models, which permits comparison with less general methods, such as principal components analysis, and with flexible models, su