Diabetes Risk Assessment Web App

web-development
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
PythonDjangoMachine Learning

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