‘A knowledge Base Data Mining Based on Parkinson's Disease

Hassan, Md. Redone; Aminul Islam, Md.; Obidul Kadir, S.K.

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dc.contributor.author	Hassan, Md. Redone
dc.contributor.author	Aminul Islam, Md.
dc.contributor.author	Obidul Kadir, S.K.
dc.date.accessioned	2020-10-04T07:37:14Z
dc.date.available	2020-10-04T07:37:14Z
dc.date.issued	2019-04-25
dc.identifier.uri	http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/4443
dc.description	Parkinson’s disease is a progressive neuro-degenerative disease which affects in our central nervous system. Our brain consists 86 billion neurons. Every neuron has his own functionality. In our mid brain have an area called substantia nigra . In this have a neuron called dopamine. Reducing dopamine neurons is the causes of being Parkinson’s disease in human body. Approximately 4-6 million people are affected by Parkinson’s disease in every year. In Bangladesh, Every year 1600 people are die by Parkinson’s disease and every year the growth rate of this disease are getting larger. The life expectancy of PD affected people is 5-10 years. But the pooled report on clinical research says that [16] accuracy of diagnosis Parkinson’s disease is only 80.6%. Till today has no recovery of [3] Parkinson’s disease(PD).In the early stage diagnosis parkinson’s disease by using some brain scans like MRI, fMRI, SPECT etc. But it can’t give the best accuracy. So for that we are come up to work with it by different approaches to improving the diagnosis of PD research that [3] in the early stage can diagnosis Parkinson’s disease(PD) by [20] Support vector Machine (SVM) , K-nearest neighbor (KNN) and Decision tree (DT). So that for medical research it can very helpful that which approaches is best for diagnosis PD by using classification technique.	en_US
dc.description.abstract	The approaches of detecting Parkinson’s disease (PD) in human body from voice data using Classification techniques apply three different algorithms for finding the growth rate of Parkinson’s disease. Support vector machine (SVM), K-nearest neighbor (K-NN) and Decision tree (DT) are applied to detect the progression rate of Parkinson’s disease (PD) by using Unified Parkinson’s disease rating scale (UPDRS) and Hoehn &Yahr scale (HYS) . Unified Parkinson’s disease rating scale (UPDRS) deals with motor fluctuations and change over voice after certain period and that can measure the people affected by Parkinson’s disease and healthy people. Hoehn & Yahr scale (HYS) are measures the symptoms which are related to progression of Parkinson’s disease (PD) in human body. Classifier algorithms used to detect the factors and symptoms which are related to progression of Parkinson’s disease (PD) in human body using voice data. The algorithms can detect Parkinson’s disease (PD) by several approaches which criteria are related to progression of Parkinson’s disease (PD) in human body. From the distinctions of all algorithms measures which algorithm give the best accuracy for several approaches to diagnosis Parkinson’s disease (PD) and risk factors of had Parkinson’s disease (PD) in human body.	en_US
dc.language.iso	en	en_US
dc.publisher	Daffodil International University	en_US
dc.subject	Data mining	en_US
dc.subject	Knowledge management	en_US
dc.subject	Parkinson's disease	en_US
dc.title	‘A knowledge Base Data Mining Based on Parkinson's Disease	en_US
dc.type	Other	en_US