Diagnosing Parkinson's Disease using Data Mining Techniques |
Author(s): |
| Rahul Zaveri , Veermata Jijabai Technological Institute, Matunga; Prof. Pramila M. Chawan, Veermata Jijabai Technological Institute, Matunga |
Keywords: |
| Data Mining, Parkinson's Disease, Decision Tree, Random Forest, Support Vector Machine |
Abstract |
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Parkinson's disease is a movement disorder of the nervous system that worsens over time. As nerve cells (neurons) in parts of the brain weaken or are damaged or die, people may begin to notice problems with movement, tremor, stiffness in the limbs or the trunk of the body, or impaired balance. As these symptoms become more obvious, people may have difficulty walking, talking, or completing other simple tasks. Not everyone with one or more of these symptoms has Parkinson's Disease, as the symptoms appear in other diseases as well. Thus, we aim to use Data Mining Techniques (K-Nearest Neighbour, Logistic Regression, Linear Regression, Decision Tree, SVM, Naive Bayes, Random Forest, Artificial Neural Networks) to determine whether a person is suffering from Stage-2 Parkinson's disease. |
Other Details |
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Paper ID: IJSRDV9I40310 Published in: Volume : 9, Issue : 4 Publication Date: 01/07/2021 Page(s): 305-307 |
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