Early Detection of Parkinson Disease Progression using Gaussian Naïve Bayes Machine Learning Approach by identifying Degeneration in Basal Ganglia Regions
Madhusudhana G K1, M B Sanjaypande2, Raveesh B N3
1Madhusudhana G K*, Research Scholar, Department of Computer Science and Engineering, VVIET, Visvesvaraya Technological University, Belagavi, India.
2Dr. M B Sanjaypande, Research Supervisor, Department of Computer Science and Engineering, VVIET, Visvesvaraya Technological University, Belagavi, India.
3Dr. Raveesh B N, Professor and Head, Department of Psychiatry, Mysore Medical College, Mysore, India.
Manuscript received on October 05, 2020. | Revised Manuscript received on October 25, 2020. | Manuscript published on October 30, 2020. | PP: 433-435 | Volume-10 Issue-1, October 2020. | Retrieval Number: 100.1/ijeat.A19221010120 | DOI: 10.35940/ijeat.A1922.1010120
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Parkinson’s Disease (PD) is a progressive neuro-degenerative disorder that affects millions of people across the globe. Analyzing volume changes in the basal ganglia seems to be a promising approach towards developing non-invasive and non-radioactive neuro-imaging markers for this disease. In this work, we report a study of classification based on the volumes of basal ganglia regions obtained from brain atlas. The study investigates the volume changes in certain anatomical structures of the basal ganglia region of PD affected subjects.
Keywords: Basal ganglia, brain atlas, neuro-degenerative disorder, Parkinson’s disease.