Research Intern, AI & Medical Imaging
- Engineered a novel hybrid deep learning model, combining Convolutional Neural Networks (CNNs) with Transformers, to significantly enhance diagnostic accuracy from medical scans.
- Pioneered the integration of Explainable AI (XAI) techniques to make the model's reasoning transparent and trustworthy for clinicians, with the research aimed at top-tier conference publication.
- Developed and deployed a full-stack medical diagnosis application using Flask and modern frontend tools, enabling real-time predictions, GradCAM visualizations, and doctor feedback integration.