Parkinson Disease Detection Using Machine Learning Algorithms
Abstract: Parkinson's disease is a global public health concern. Nerve cells, the building blocks of the nervous system in the brain stop producing when they are damaged. Thus, less dopamine is produced that inhibits motor skills and speech. Voice changes in the first stage before brain cells are affected, hence helps identify Parkinson's disease in the early stages and therefore prevent brain cell damage that can lead to reduced fusion and movement. Introduction of different ML algorithms for classification of Parkinson's disease is presented.
Keywords: Parkinson's Disease, Machine Learning, Computer Science, KNN, SVM, Regression, RF, Decision Tree
How to Cite?: Yatharth Nakul, Ankit Gupta, Hritik Sachdeva, "Parkinson Disease Detection Using Machine Learning Algorithms", Volume 10 Issue 6, June 2021, International Journal of Science and Research (IJSR), Pages: 314-318, https://www.ijsr.net/getabstract.php?paperid=SR21530012948, DOI: https://dx.doi.org/10.21275/SR21530012948