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Author Acampora, G. ♦ Kiseliova, T. ♦ Pagava, K. ♦ Vitiello, A.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2011
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Diseases ♦ Pragmatics ♦ Medical diagnostic imaging ♦ XML ♦ Fuzzy sets ♦ Fuzzy systems ♦ Rare diseases ♦ Fuzzy Systems ♦ Fuzzy Markup Language ♦ Medical Diagnosis
Abstract In this paper we present the preliminary results of application of Fuzzy Markup Language (FML) to suspect a non-common disease. Under non-common diseases we understand rare diseases. From the broad point of view this problem belongs to the computer-assisted decision support in medical diagnostics and can be supported by fuzzy logic controllers. We can use conventional methods to diagnose a rare disease if it can be exhibited by outstanding symptoms. For example, there are several search machines and data banks that allow to find a rare disease clearly exhibited by a patient's symptoms/signs. But it is very difficult to diagnose a rare disease if it masks as a common disease. Diagnostic of rare diseases is connected with lack, uncertainty and imprecision of knowledge, medical mistake and even medical failure. Additionally, very often a common disease is also established with some degree of belief, thus, the expressions such as “it is possible that a patient has a particular disease” rather often present in the daily medical practice. It is clear that if we would know the common diseases, then deviations from them can be considered as a sign of non-common diseases. In this paper we investigate such deviations with the help of FML. We show how FML mechanism can be adjusted to suspect a rare disease, and discuss the appropriateness of the available operators.
Description Author affiliation: Child and Adolescent Medicine, Tbilisi Medical State University, Tbilisi, Georgia 0177 (Pagava, K.) || Dept. of Computer Sciences, Ivane Javakhishvili Tbilisi State University, Tbilisi, Georgia 0143 (Kiseliova, T.) || Dept. of Computer Science, University of Salerno, Fisciano, Salerno 84084 (Acampora, G.; Vitiello, A.)
ISBN 9781424473151
ISSN 10987584
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2011-06-27
Publisher Place Taiwan
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781424473175
Size (in Bytes) 323.21 kB
Page Count 7
Starting Page 2073
Ending Page 2079

Source: IEEE Xplore Digital Library