Keywords: Parkinson's Disease, Machine Learning/Artificial Intelligence, white matter connectivity, DTI, prediction modelIn this study, the machine learning method was used to establish a prediction model for Parkinson’s disease(PD) progression by using white matter connectivity and clinical information. A total of 123 PD patients were included. White matter network connection analysis and clinical information collection were performed for each patient. The results showed that combined with the white matter connection and clinical features, a good model of PD disease progression was established. White matter network connectivity helps predict PD progression at the individual level.
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