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Personalized Data-Driven Robust Machine Learning Models to Differentiate Parkinson's Disease Patients Using Heterogeneous Risk Factors

2025-12-19 neurology Title + abstract only
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Parkinsons Disease (PD) is the most prevalent neurodegenerative disorder after Alzheimers, yet its diagnosis largely relies on subjective clinical assessments. Thus, this study proposes a systematic, data-driven approach to accurately classify PD patients using heterogeneous risk factors along with efficient machine learning. Six machine learning algorithms, Support Vector Machine(SVM), Random Forest(RF), Extreme Gradient Boosting(XGBoost), Logistic Regression(LR), K-Nearest Neighbour (KNN), and...

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