Parkinson’s Disease Detection

Parkinson’s Disease (PD) is a progressive neurodegenerative disorder affecting millions globally, characterized by tremors, stiffness, slowness, and impaired balance. Early detection of PD is crucial for effective diagnosis and management. This project, "Parkinson’s Disease Detection Using Deep Learning Techniques," aims to develop a machine learning model utilizing Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) and Random Forest to analyze speech features from the dataset provided. By focusing on speech characteristics such as frequency, intensity, and timing, the project seeks to improve diagnostic accuracy and support clinical decision-making. The model's implementation could lead to early PD detection, offering benefits such as better treatment options, enhanced patient quality of life, and reduced healthcare costs. Additionally, an frequently ask question related to Parkinson’s Disease.

Keywords: Parkinson’s Disease, Speech Analysis, Deep Learning, Convolutional Neural Networks, Support Vector Machines, Early Detection, Diagnostic Accuracy, Machine Learning, Healthcare.