Early Detection of Parkinson's disease using a Machine Learning-Based Framework for Differentiating the Disease's with Various Stages

Abstract

The term "Parkinson's disease" (PD) is mostly brought on by a disturbance of a brain's dopamine-producing cells, a chemical which permits communication between brain cells. Brain cells that produce dopamine control movement, flexibility, and fluency. After 60% to 80% of these cells are gone, dopamine production is inhibited, and Parkinson's disease symptoms start to emerge. Researchers are concentrating their efforts on finding any early non-movement symptoms to stop the disease's development because it is thought that the disease starts many years before any evident movement-related indicators occur. Early correct diagnosis of the condition is crucial to halt the continuous advancement of Parkinson's disease and give people access to medications that can slow the disease. To do this, ongoing research into the premotor stage of Parkinson's disease is necessary.