Xception model for efficient Parkinson's disease detection and prediction

Parkinson’s disease affects movement due to loss of dopamine-producing brain cells. This project used deep learning with the Xception model on Kaggle clinical data to detect the disease early. After selecting key features, the model achieved 100% training and 97% test accuracy, showing strong potential for early diagnosis and treatment planning.