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Artificial intelligence diagnostics in psychophysiological medicine

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Licentiate Thesis Proposal

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Report


Abstract

This is a proposal of the content of a licentiate degree in computer science at Mälardalen University, Sweden. The contents of this licentiate thesis are concerning the use of Artificial Intelligence (AI) for classification of complex measurements. Measurements targeted in this research have previously only been classified by domain specialists. The reason for this is the complexity of the classification process. A method has been developed to accomplish this classification. The method is mainly based on Case-Based Reasoning but uses a number of other techniques. Both AI methods and mathematical methods are used for feature identification. The system is classifying continuous non-stationary measurements, and has the capacity to improve performance with a growing number of solved cases. A system based on the proposed method is implemented for a clinical application (in psychophysiological medicine) as proof of concept and for evaluation purposes.

Bibtex

@techreport{Nilsson491,
author = {Markus Nilsson},
title = {Artificial intelligence diagnostics in psychophysiological medicine},
note = {Licentiate Thesis Proposal},
month = {September},
year = {2003},
url = {http://www.es.mdh.se/publications/491-}
}