Feature selection and machine learning methods for optimal identification and prediction of subtypes in Parkinson's disease

•We explored hybrid ML systems including selector algorithms and classifiers.•Radiomics features are important for classification and clustering tasks.•The high score features selected by ensemble voting are not effective.•The features directly selected via selector algorithms are more important. Th...

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Veröffentlicht in:	Computer methods and programs in biomedicine 2021-07, Vol.206, p.106131-106131, Article 106131
Hauptverfasser:	Salmanpour, Mohammad R., Shamsaei, Mojtaba, Rahmim, Arman
Format:	Artikel
Sprache:	eng
Schlagworte:	Ensemble Voting Feature Selection Algorithms Outcome prediction Parkinson's disease Radiomics Subtype identification
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