My Projects
A selection of projects that demonstrate my technical skills, creativity, and problem-solving approach.
🩺 Lymphography Disease Prediction (Explainable AI)
Problem: Medical diagnosis using lymphography data is complex and traditional ML models lack interpretability.
Solution: Developed and evaluated multiple classification models (KNN, Decision Tree, Random Forest) and applied SHAP (Explainable AI) to interpret feature importance.
Impact: Improved transparency and trust in medical predictions, making the system suitable for research and academic use.
Tech Stack: Python, Scikit-learn, SHAP
🩸 Daily Sugar Guidance Web Application
Problem: People with diabetes often struggle to understand daily blood sugar readings and required lifestyle actions.
Solution: Built and deployed a Streamlit-based web application that provides daily diet and walking guidance based on blood sugar values, including safe input validation and emergency handling.
Impact: Created an accessible and easy-to-use tool suitable for both literate and low-literacy users.
Tech Stack: Python, Streamlit, GitHub, Streamlit Cloud