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 systemPublication year: 2006Abstract: 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
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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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header:
identifier: oai:dalea.du.se:1916
datestamp: 2021-04-15T12:05:54Z
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recordContentSource: du
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
language:
languageTerm: eng
genre:
conference/other
ref
note:
Published
5
name:
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type: personal
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Ahmed
Mobyen
role:
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authority: du
namePart:
Westin
Jerker
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affiliation:
Högskolan Dalarna
Datateknik
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jwe
0000-0003-0403-338X
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Nyholm
Dag
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type: personal
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namePart:
Dougherty
Mark
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Högskolan Dalarna
Datateknik
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Groth
Torgny
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originInfo:
dateIssued: 2006
place:
placeTerm: Umeå
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titleInfo:
title: 23rd annual workshop of the Swedish Artificial Intelligence Society
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titleInfo:
title: Report / UMINF
identifier: 0348-0542
location:
url: http://du.diva-portal.org/smash/get/diva2:521576/FULLTEXT01.pdf
accessCondition: gratis
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typeOfResource: text