Authors: Reeda Kunhimangalam Sujith Ovallath Paul K Joseph
Publish Date: 2014/04/02
Volume: 38, Issue: 4, Pages: 38-
Abstract
The prevalence of peripheral neuropathy in general population is ever increasing The diagnosis and classification of peripheral neuropathies is often difficult as it involves careful clinical and electrodiagnostic examination by an expert neurologist In developing countries a large percentage of the disease remains undiagnosed due to lack of adequate number of experts In this study a novel clinical decision support system has been developed using a fuzzy expert system The study was done to provide a solution to the demand of systems that can improve health care by accurate diagnosis in limited time in the absence of specialists It employs a graphical user interface and a fuzzy logic controller with rule viewer for identification of the type of peripheral neuropathy An integrated medical records database is also developed for the storage and retrieval of the data The system consists of 24 input fields which includes the clinical values of the diagnostic test and the clinical symptoms The output field is the disease diagnosis whether it is Motor Demyelinating/Axonopathy neuropathy sensory Demyelinating/Axonopathy neuropathy mixed type or a normal case The results obtained were compared with the expert’s opinion and the system showed 9327 accuracy The study aims at showing that Fuzzy Expert Systems may prove useful in providing diagnostic and predictive medical opinions It enables the clinicians to arrive at a better diagnosis as it keeps the expert knowledge in an intelligent system to be used efficiently and effectively
Keywords: