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A web enabled fuzzy rule-based decision support system for dose adjustments of Duodopa infusion to patients with advanced Parkinsons disease

Fulltext:


Publication Type:

Student Thesis


Abstract

The main purpose of this thesis work was to develop a web enabled decision support system (DSS) based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson’s disease, given data from motor state assessments and dosage. One data set was used for tuning the FIS and another data set was used for evaluating performance compared with actual given dose. Further, a web application with an interactive graphical user interface that presented alerts indicating non optimal dosage, dose summary information, advice for new dosage and options to calculate initial dose and evaluation of the DSS was implemented. Goodness-of-fit for the new patients (Observation data) was 65% for ongoing patients (Duodopa Infusion - Randomized Efficacy and Quality of life Trial study data) it was 98%. From the result of the system evaluation, it was found that the DSS could achieve expert’s knowledge on an average 81% accurately. User evaluation, i.e. assessment of the DSS that it does the right thing right, an important step is needed to be done before implementing the DSS. The system incorporated the human knowledge to make a decision; it could work as an assistant of the clinical staffs in advanced Parkinson’s disease.

Bibtex

@mastersthesis{Ahmed1310,
author = {Mobyen Uddin Ahmed},
title = {A web enabled fuzzy rule-based decision support system for dose adjustments of Duodopa infusion to patients with advanced Parkinsons disease},
number = {Nr: E3244D},
month = {November},
year = {2005},
url = {http://www.es.mdu.se/publications/1310-}
}