This project will involve developing an AI model to analyze a dataset of approximately 27,000 anonymized eye images collected during the COVID-19 pandemic. The model aims to detect and diagnose medical conditions such as hypertension and diabetes based on retinal images. By participating in this project, students will gain hands-on experience in machine learning, deep learning, and medical image analysis while contributing to a real-world healthcare application.

• Data Preprocessing: Clean and preprocess medical images for AI model training, ensuring data consistency and quality.
• Feature Engineering: Identify and extract relevant image features that can contribute to accurate disease detection.
• Model Development: Build and train an AI model using Python and TensorFlow to classify and diagnose eye-related conditions.
• Model Evaluation & Optimization: Assess model accuracy using validation techniques and optimize performance using tuning methods.
• Final Report & Deployment Recommendations: Deliver a final report detailing the model's effectiveness, potential improvements, and real-world deployment considerations.