Computational Intelligence Methods on Biomedical Signal Analysis

This book is centered around the development and
application of computationally effective
solutions based on artificial neural networks (ANN)
for biomedical signal analysis and data
mining on medical records. The description of some
ANN types is followed by the description of a new
model design for pattern classification. A detailed
description of the wavelets theory is included
together with an example of it''s practical use for
feature pre-processing. In the field of Biomedical
Engineering, the goal of a researcher is to provide
the clinician with the best possible
information needed to make an accurate diagnosis.
The new learning paradigms proposed, based on
semi-supervised learning are imposing themselves as
an emergent powerful modeling methodology to be
applied not only on unidimensional medical signals
(like ECG or EEG signals) but also in image analysis
and many other engineering fields.

Autorentext

Education: BSc (Honors) in Computer Science from University ofCraiova, Romania in 1988MSc in Biomedical Engineering, University of Patras, Greece, 1999PhD from the Inter-University Program of Postgraduate studiesfrom Universities of Athens and Patras-Greece in 2004Postdoctoral studies at University of South Carolina & DublinCity University

Klappentext

This book is centered around the development and application of computationally effective solutions based on artificial neural networks (ANN) for biomedical signal analysis and data mining on medical records. The description of some ANN types is followed by the description of a new model design for pattern classification. A detailed description of the wavelets theory is included together with an example of it''s practical use for feature pre-processing. In the field of Biomedical Engineering, the goal of a researcher is to provide the clinician with the best possible information needed to make an accurate diagnosis. The new learning paradigms proposed, based on semi-supervised learning are imposing themselves as an emergent powerful modeling methodology to be applied not only on unidimensional medical signals (like ECG or EEG signals) but also in image analysis and many other engineering fields.