Parkinson’s Disease Detection

This study uses convolutional neural networks (CNNs) to accurately detect early Parkinson’s disease (PD) from SPECT imaging, including challenging SWEDD cases where scans appear normal. By leveraging image-based features, the model distinguishes early PD and SWEDD patients from healthy controls with high accuracy. These results demonstrate the potential of CNN-based analysis to enhance early PD diagnosis and reduce reliance on subjective clinical interpretation.