Interactive Data Analysis Tool for Diabetes Risk in Healthcare
This project developed a visual analytics platform designed for healthcare professionals to investigate the relationships between various factors and diabetes risk, leveraging data from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) dataset.
The tool supports high-risk group identification, what-if analysis, and individual risk assessment. Core algorithms include Mutual Information and XGBoost.
The technology stack comprises Python, FastAPI, Vue.js, D3.js, and Plotly.
My contributions include frontend design and full-stack development.
