Ethio-MeditechScan: Medical Image Analysis with

Ethio-MeditechScan: Medical Image Analysis with AI

I engineered this end-to-end medical diagnostic tool to improve the speed and accuracy of healthcare delivery in Ethiopia. The system uses Deep Learning (CNNs) to classify medical images and provide instant insights to healthcare professionals.

Key Technical Features:

AI Engine: Developed a high-performance Convolutional Neural Network (CNN) using TensorFlow and Keras for accurate image classification.

Full-stack Interface: Built a responsive React dashboard that allows doctors to upload scans (X-rays/MRIs) and view AI-driven diagnostic reports in real-time.

Data Processing: Performed extensive data cleaning and augmentation on medical datasets to ensure the model's robustness and reliability.

API Integration: Engineered a FastAPI/Flask backend to serve the model and handle image processing requests with low latency.

This project highlights my ability to bridge the gap between complex Artificial Intelligence research and practical, user-facing medical software.