COMPREHENSIVE MACHINE LEARNING AND DEEP LEARNING APPROACHES FOR PARKINSON'S DISEASE CLASSIFICATION AND SEVERITY ASSESSMENT

COMPREHENSIVE MACHINE LEARNING AND DEEP LEARNING APPROACHES FOR PARKINSON'S DISEASE CLASSIFICATION AND SEVERITY ASSESSMENT

In this study, we aimed to adopt a comprehensive approach to categorize and assess the severity of Parkinson's disease by leveraging techniques from both machine learning and deep learning. We thoroughly evaluated the effectiveness of various models, including XGBoost, Random Forest, Multi-Lay...

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Bibliographic Details
Main Authors: Oumaima Majdoubi, Achraf Benba, Ahmed Hammouch
Format: Article
Language:English
Published: Lublin University of Technology 2023-12-01
Series:Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
Subjects:
Parkinson's disease
severity assessment
machine learning
XGBoost
Gated Recurrent Unit (GRU)
comparative analysis
Online Access:https://ph.pollub.pl/index.php/iapgos/article/view/5309

Internet

https://ph.pollub.pl/index.php/iapgos/article/view/5309

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