Parkinson’s disease detection using machine learning
International Journal of Development Research
Parkinson’s disease detection using machine learning
Received 17th January, 2022 Received in revised form 27th February, 2022 Accepted 20th March, 2022 Published online 22nd April, 2022
Copyright©2022, Shikha Singh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Parkinson's disease is a condition in which dopamine-producing cells in the brain die. Parkinson's disease symptoms appear as the amount of dopamine in the brain diminishes. Parkinson's disease is a slow-progressing condition with symptoms such as tremors in the hands, arms, legs, chin, and face that get worse with time. People may have trouble walking and speaking as the condition advances. Although there is no cure for Parkinson's disease, the symptoms of the disease can be alleviated with the use of some medications. There are a number of common symptoms that may or may not suggest that the patient has Parkinson's disease. In this study, a new rating system was developed to aid in determining the severity of Parkinson's disease. However, a person with identical symptoms does not necessarily have Parkinson's disease. Because Parkinson's disease is an unsolved problem, the study focuses. On relevant aspects, medicines, and common approaches used to identify or assess the disease. Patients with Parkinson's disease often experience voice difficulties in the early stages of the condition. As a result, recent investigations for the identification of Parkinson's disease have focused on diagnosis systems based on voice disturbances.