PARKINSON’S DISEASE DIAGNOSIS BASED ON THE CONVOLUTIONAL NEURAL NETWORK AND PARTICLE SWARM

Both men and women are affected by Parkinson's disease. Parkinson's disease is a brain illness that causes tremors, stiffness, and difficulties with walking, balance, and coordination. Only 15% of people under the age of 50 are diagnosed with the condition, which is diagnosed around the age of 65. The Convolutional Neural Network and Particle Swarm Optimization Algorithm were used to assess and detect Parkinson's Disease in this study. To reduce the amount of features, the Particle Swarm Optimization approach is utilised, and the best features are chosen. Two approaches are utilised to evaluate the results: Mean Square Error and Root Mean Square Error. Mean Square Error and Root Mean Square Error had detection rates of 0.32 and 95.77, respectively.

Please see the link :- https://www.ikprress.org/index.php/AJOMCOR/article/view/6306