A full-stack web application that predicts a user's risk of developing diabetes based on personal health data. Built with Django and a Python machine learning backend, the app offers a clean medical-style form interface for inputting key health indicators.
Input features collected:
Personal information — gender and age group
Health indicators — hypertension history, heart disease history, and smoking status
Medical measurements — BMI, HbA1c level, and blood glucose level
Key highlights:
ML-powered prediction — a trained classification model (e.g. Random Forest, Logistic Regression) processe
