Using Fuzzy Evidential Reasoning for Multiple Assessment Fusion in Spondylarthropathic Patient Self-Management

dc.cclicenceCC-BY-NCen
dc.contributor.authorSchiboni, Giovannien
dc.contributor.authorLeister, Wolfgangen
dc.contributor.authorChen, Limingen
dc.date.accessioned2017-03-20T16:07:17Z
dc.date.available2017-03-20T16:07:17Z
dc.date.issued2016-06-07
dc.description.abstractThis paper proposes an approach for an ICT-supported medical assessment, by merging measures of signs and symptoms from heterogeneous sources. The disease status estimate of patients that suffer from spondylarthropathy is evaluated with different types of uncertainties using a fuzzy rule-based evidential reasoning (FURBER) approach. The approach treats measures of signs and symptoms in order to define the disease status. We take in consideration the Bath indices and the ASDAS index, described by using fuzzy linguistic variables. A fuzzy rule-base designed on the basis of a belief structure is exploited to capture uncertainty and non-linear relationships between these parameters and the disease status. The inference of the rule-based system is implemented using an evidential reasoning algorithm. An expected utility-based health score is used to assess disease activity over time and to measure the response to treatment. Our tool may be particularly helpful in monitoring the response of treatments and in interpreting the response to therapeutic interventions in clinical trials. A case study is used to illustrate the application of the proposed approach.en
dc.funderN/Aen
dc.identifier.citationSchiboni, G., Leister, W. and Chen, L. (2016) Using Fuzzy Evidential Reasoning for Multiple Assessment Fusion in Spondylarthropathic Patient Self-Management. Emerging Trends and Advanced Technologies for Computational Intelligence, Volume 647 of the series Studies in Computational Intelligence, Springer, 647, pp 15-39en
dc.identifier.doihttps://doi.org/10.1007/978-3-319-33353-3_2
dc.identifier.isbn9783319333519
dc.identifier.urihttp://hdl.handle.net/2086/13759
dc.peerreviewedYesen
dc.projectidN/Aen
dc.publisherSpringeren
dc.researchinstituteCyber Technology Institute (CTI)en
dc.subjectSpondyloarthritisen
dc.subjectMedical assessmenten
dc.subjectMultiple attribute decision analysisen
dc.subjectFuzzy rule-baseen
dc.subjectEvidential reasoningen
dc.subjectUncertainty modellingen
dc.titleUsing Fuzzy Evidential Reasoning for Multiple Assessment Fusion in Spondylarthropathic Patient Self-Managementen
dc.typeBook chapteren

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