Predicting Optimal Deep Brain Stimulation Parameters for Parkinson's Disease using Functional MRI and MSVM-Reference-Cited by-同舟云学术

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Predicting Optimal Deep Brain Stimulation Parameters for Parkinson's Disease using Functional MRI and MSVM

Published:2024-03-15 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 International Conference on Distributed Computing and Optimization Techniques (ICDCOT)
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Author:

Muruganandham S K¹,Krithika S²,Alsalami Zaid³,Kumar S Pradeep⁴,Malathy V⁵

Affiliation:

1. Raja Rajeswari college of engineering,Computer applications,Bengaluru,India

2. Nandha Engineering College,Department of CSE (Cyber Security),Erode,Tamilnadu,India

3. The Islamic university,Najaf,Iraq

4. Nitte Meenakshi Institute of Technology,Department of ECE,Bengaluru,India

5. SR University,Department of ECE,Warangal,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10515307/10515308/10515568.pdf?arnumber=10515568

Reference12 articles.

1. Detection of Brain Abnormalities in Parkinson’s Rats by Combining Deep Learning and Motion Tracking

2. Spectrum Sensing Based on Hybrid Spectrum Handoff in Cognitive Radio Networks

3. Diagnostic classification of Parkinson’s disease based on non-motor manifestations and machine learning strategies

4. Application of a new machine learning model to improve earthquake ground motion predictions

5. Improved motor outcome prediction in Parkinson's disease applying deep learning to DaTscan SPECT images

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