Feature Selection Algorithms Applied to Parkinson's Disease

TitleFeature Selection Algorithms Applied to Parkinson's Disease
Publication TypeConference Paper
Year of Publication2001
AuthorsNavío, M., Aguilera José, del Jesus M. J., González R., Herrera F., and Iríbar C.
EditorCrespo, Jose, Maojo Victor, and Martin Fernando
Conference NameMedical Data Analysis
PublisherSpringer Berlin Heidelberg
Conference LocationBerlin, Heidelberg
ISBN Number978-3-540-45497-7

In Parkinson's Disease an analysis of Medical Data could highlight some symptoms, which can be used as a complementary tool in an early diagnosis. This paper analyses some Filter and Wrapper Feature Selection Algorithms and combinations of them that determine some relevant features in relation to this problem. The experimentation carried out with a data set of patients allows us to determine a set of different premorbid personality traits that can be considered in the early diagnosis of Parkinsonism.