Early Parkinson’s disease identification via hybrid feature selection from multi-feature subsets and optimized CatBoost with SMOTE
Achieving high accuracy, efficiency and robustness remains a primary challenge in Parkinson's disease (PD) detection, as existing methods often struggle with these aspects. Additionally, data imbalance in medical datasets further limits the reliability of current models. Given the critical role...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Systems Science & Control Engineering |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/21642583.2025.2498909 |
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