A fuzzy rule-based decision support system for Duodopa treatment in Parkinson

Document identifier: oai:dalea.du.se:1916
Keyword: Fuzzy logic, Decision support system, Parkinson, Duodopa, Levodopa infusion, Fuzzy inference system
Publication year: 2006
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Abstract:

A decision support system (DSS) was implemented based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson’s disease, using data from motor state assessments and dosage. Three-tier architecture with an object oriented approach was used. The DSS has a web enabled graphical user interface that presents alerts indicating non optimal dosage and states, new recommendations, namely typical advice with typical dose and statistical measurements. One data set was used for design and tuning of the FIS and another data set was used for evaluating performance compared with actual given dose. Overall goodness-of-fit for the new patients (design data) was 0.65 and for the ongoing patients (evaluation data) 0.98. User evaluation is now ongoing. The system could work as an assistant to clinical staff for Duodopa treatment in advanced Parkinson’s disease.

Authors

Mobyen Ahmed

Other publications >>

Jerker Westin

Högskolan Dalarna; Datateknik
Other publications >>

Dag Nyholm

Other publications >>

Mark Dougherty

Högskolan Dalarna; Datateknik
Other publications >>

Torgny Groth

Other publications >>

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        identifier: oai:dalea.du.se:1916
        datestamp: 2021-04-15T12:05:54Z
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                recordCreationDate: 2006-03-07
            identifier: http://urn.kb.se/resolve?urn=urn:nbn:se:du-1916
            titleInfo: 
                @attributes: 
                    lang: eng
                title: A fuzzy rule-based decision support system for Duodopa treatment in Parkinson
            abstract: 
A decision support system (DSS) was implemented based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson’s disease using data from motor state assessments and dosage. Three-tier architecture with an object oriented approach was used. The DSS has a web enabled graphical user interface that presents alerts indicating non optimal dosage and states new recommendations namely typical advice with typical dose and statistical measurements. One data set was used for design and tuning of the FIS and another data set was used for evaluating performance compared with actual given dose. Overall goodness-of-fit for the new patients (design data) was 0.65 and for the ongoing patients (evaluation data) 0.98. User evaluation is now ongoing. The system could work as an assistant to clinical staff for Duodopa treatment in advanced Parkinson’s disease.

            subject: 
                    @attributes: 
                        lang: eng
                    topic: Fuzzy logic
                    @attributes: 
                        lang: eng
                    topic: decision support system
                    @attributes: 
                        lang: eng
                    topic: Parkinson
                    @attributes: 
                        lang: eng
                    topic: Duodopa
                    @attributes: 
                        lang: eng
                    topic: levodopa infusion
                    @attributes: 
                        lang: eng
                    topic: fuzzy inference system
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                languageTerm: eng
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                conference/other
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                        Mobyen
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                dateIssued: 2006
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                    placeTerm: Umeå
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                    titleInfo: 
                        title: 23rd annual workshop of the Swedish Artificial Intelligence Society 
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                        type: series
                    titleInfo: 
                        title: Report / UMINF
                    identifier: 0348-0542
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                url: http://du.diva-portal.org/smash/get/diva2:521576/FULLTEXT01.pdf
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