Parkinson'S Disease

Parkinson's Disease (PD) research focuses on developing accurate and accessible diagnostic tools, primarily targeting early detection to enable timely intervention. Current efforts leverage diverse data sources, including speech, gait analysis from video and wearable sensors, EEG, and MRI scans, employing machine learning models such as convolutional neural networks (CNNs), graph convolutional networks (GCNs), transformers, and ensemble methods for classification and severity prediction. These advancements aim to improve diagnostic accuracy, reduce reliance on subjective clinical assessments, and facilitate earlier and more efficient PD diagnosis, ultimately improving patient outcomes and healthcare resource allocation. The development of accessible at-home diagnostic tools is a particularly significant area of focus.