Abstract
Thalassemia and anemia are common blood disorders that require early detection to avoid serious complications. This project proposes an automated system using the VGG16 model to analyze blood smear images. The system identifies patterns and classifies diseases accurately. It also generates a precautionary report with results and recommendations. This approach improves diagnostic speed, reduces human error, and supports better patient care.
Keywords:This project focuses on anemia and thalassemia, common blood disorders that need early detection. It uses blood smear images and deep learning, specifically the VGG16 model, to classify images and predict diseases accurately.