Automated Medical Image Analysis Pipeline with Domain Generalization

Developed a deep learning pipeline that classifies retinal fundus images across multiple disease categories, trained to generalize across unseen datasets using leave-one-domain-out evaluation. Built with PyTorch and deployed as an interactive Streamlit application. Part of active ML research exploring cross-dataset robustness for medical imaging. Combines research-grade methodology with production deployment.