Early diagnosis of Parkinson's disease using machine learning algorithms

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dc.authoridSenturk, Zehra Karapinar/0000-0003-3116-1985
dc.authorwosidSenturk, Zehra Karapinar/P-7435-2017
dc.contributor.authorSenturk, Zehra Karapinar
dc.date.accessioned2021-12-01T18:47:19Z
dc.date.available2021-12-01T18:47:19Z
dc.date.issued2020
dc.department[Belirlenecek]en_US
dc.description.abstractParkinson's disease is caused by the disruption of the brain cells that produce substance to allow brain cells to communicate with each other, called dopamine. The cells that produce dopamine in the brain are responsible for the control, adaptation and fluency of movements. When 60-80%of these cells are lost, then enough dopamine is not produced and Parkinson's motor symptoms appear. It is thought that the disease begins many years before the motor (movement related) symptoms and therefore, researchers are looking for ways to recognize the nonmotor symptoms that appear early in the disease as early as possible, thereby halting the progression of the disease. In this paper, machine learning based diagnosis of Parkinson's disease is presented. The proposed diagnosis method consists of feature selection and classification processes. Feature Importance and Recursive Feature Elimination methods were considered for feature selection task. Classification and Regression Trees, Artificial Neural Networks, and Support Vector Machines were used for the classification of Parkinson's patients in the experiments. Support Vector Machines with Recursive Feature Elimination was shown to perform better than the other methods. 93.84% accuracy was achieved with the least number of voice features for Parkinson's diagnosis.en_US
dc.identifier.doi10.1016/j.mehy.2020.109603
dc.identifier.issn0306-9877
dc.identifier.issn1532-2777
dc.identifier.pmid32028195en_US
dc.identifier.scopus2-s2.0-85078757871en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1016/j.mehy.2020.109603
dc.identifier.urihttps://hdl.handle.net/20.500.12684/10228
dc.identifier.volume138en_US
dc.identifier.wosWOS:000523642300001en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakPubMeden_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorSenturk, Zehra Karapinar
dc.language.isoenen_US
dc.publisherChurchill Livingstoneen_US
dc.relation.ispartofMedical Hypothesesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDecision support systemsen_US
dc.subjectFeature selectionen_US
dc.subjectMachine learningen_US
dc.subjectMedical diagnosisen_US
dc.subjectSupport Vector Machinesen_US
dc.subjectClassificationen_US
dc.subjectPredictionen_US
dc.titleEarly diagnosis of Parkinson's disease using machine learning algorithmsen_US
dc.typeArticleen_US

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