Developed a high-performance medical diagnostic tool that utilizes Deep Learning to detect Alzheimer’s disease from MRI scans. This project bridges the gap between complex AI research and practical healthcare applications.
Key Achievements:
High-Accuracy Model: Built and optimized a Convolutional Neural Network (CNN) using TensorFlow/Keras, achieving a 95% accuracy rate on medical imaging data.
End-to-End Development: Engineered a modern, user-friendly Desktop GUI using Python and CustomTkinter, allowing healthcare professionals to perform real-time image processing without technical expertise.
Deployment-Ready: Implemented efficient preprocessing and inference pipelines to ensure rapid and reliable diagnostic results.
