A Random Forest Method to Detect Parkinson’s Disease via Gait Analysis

Author:

Açıcı Koray,Erdaş Çağatay Berke,Aşuroğlu Tunç,Toprak Münire Kılınç,Erdem Hamit,Oğul Hasan

Publisher

Springer International Publishing

Cited by 41 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Detecting the symptoms of Parkinson’s disease with non-standard video;Journal of NeuroEngineering and Rehabilitation;2024-05-03

2. IoT-driven augmented reality and virtual reality systems in neurological sciences;Internet of Things;2024-04

3. Parkinson’s Disease Diagnosis: Integrating Decision Trees and Random Forest;2024 11th International Conference on Computing for Sustainable Global Development (INDIACom);2024-02-28

4. Selection of Gait Parameters for Differential Diagnostics of Patients With De Novo Parkinson's Disease;Advances in Medical Technologies and Clinical Practice;2024-02-23

5. Assessment of Parkinson’s Disease Severity Using Gait Data: A Deep Learning-Based Multimodal Approach;Communications in Computer and Information Science;2024

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