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Author Guidi, G. ♦ Pettenati, M.C. ♦ Miniati, R. ♦ Iadanza, E.
Sponsorship IEEE Eng. Medicine Biol. Soc.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2012
Language English
Subject Domain (in DDC) Technology ♦ Medicine & health ♦ Engineering & allied operations
Subject Keyword Heart ♦ Hafnium ♦ Artificial neural networks ♦ Support vector machines ♦ Accuracy ♦ Training ♦ Artificial intelligence
Abstract In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.
Description Author affiliation: ICON (Int. Center of Comput. Neurophotonics) Found., Florence, Italy (Pettenati, M.C.) || Dept. of Electron. & Telecommun., Univ. of Florence, Florence, Italy (Guidi, G.; Miniati, R.; Iadanza, E.)
ISBN 9781424441198
ISSN 1557170X
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2012-08-28
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781457717871
Size (in Bytes) 481.42 kB
Page Count 4
Starting Page 2210
Ending Page 2213

Source: IEEE Xplore Digital Library