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Tomography, Volume 10, Issue 6
June 2024 - 9 articles
Cover Story: Parkinson’s disease (PD) is a neurodegenerative disorder characterized by dopamine depletion and alterations in neural structures. In this study, we propose a methodology that combines Causal Forest and Machine Learning to analyze resting-state functional Magnetic Resonance Imaging signals and establish classifications in regard to PD patients and healthy participants. Additionally, we provide insight by leveraging statistical tools like Multiple Correspondence Analysis to visualize the associations between brain regions and groups. The aim of this work is to provide high-accuracy classification and interpretability in PD detection using a data-driven approach that could be further used for analyzing different neurodegenerative disorders in the future. View this paper
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Tomography - ISSN 2379-139XCreative Common CC BY license