Deep Learning Based Diagnosis of Parkinson's Disease Using CNN

Authors

  • Dr. Shubhangi D C  Chairman & Professor, Department of Studies in Computer Science and Engineering, VTU, CPGS, Kalaburagi, Karnataka, India
  • Pooja Gundagurti  Student, Department of Studies in Computer Science and Engineering, VTU, CPGS, Kalaburagi, Karnataka, India

DOI:

https://doi.org//10.32628/CSEIT2062105

Keywords:

Parkinson's disease, MRI, Deep learning, Convolutional neural networks, AlexNet

Abstract

Parkinson's disease is the degenerative disease caused by loss of dopamine producing neurons. PD is characterized by gradual degradation of motor function in the brain. In this, deep learning is used to diagnose the PD patients by means of Convolutional Neural Networks (CNN). The CNN architecture ALexNet is used to refine the diagnosis of Parkinson’s disease. The MR images are trained by the transfer learned network along with the KNN algorithm to give the accuracy measures.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2020-04-30

Issue

Volume 6, Issue 2, March-April-2020

Section

Research Articles

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Copyright (c) IJSRCSEIT

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dr. Shubhangi D C, Pooja Gundagurti, " Deep Learning Based Diagnosis of Parkinson's Disease Using CNN, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 2, pp.351-355, March-April-2020. Available at doi : https://doi.org/10.32628/CSEIT2062105