The Diabetes Risk Predictor is an intelligent healthcare application that helps identify potential diabetes risk in patients. Using advanced machine learning algorithms, it analyzes various health parameters to provide quick and accurate risk assessments.

• User-Friendly Interface: Easy-to-use web interface for inputting patient data
• Real-Time Predictions: Instant diabetes risk assessment
• High Accuracy: Utilizes Gradient Boosting for reliable predictions
• Data Visualization: Clear presentation of results and insights
• Privacy-Focused: No data storage, all calculations done in real-time

The model considers several key health indicators:

• Gender
• Age
• Hypertension status
• Heart disease history
• Smoking history
• BMI (Body Mass Index)
• HbA1c level
• Blood glucose level

• Frontend: Streamlit
• Backend: Python
• ML Libraries:
  • scikit-learn
  • pandas
  • numpy
• Visualization:
  • matplotlib
  • seaborn

Try the live application: Diabetes Predictor App

1. Clone the repository:

git clone https://github.com/yourusername/Diabetes-Predictor.git

2. Install required packages:

pip install -r requirements.txt

3. Run the application:

streamlit run app.py

• Algorithm: Gradient Boosting Classifier
• Training Data: Balanced dataset of diabetic and non-diabetic patients
• Accuracy: ~85-90% (varies with data)
• Validation: Cross-validation techniques applied

This tool is designed for preliminary screening only and should not replace professional medical advice. Always consult healthcare professionals for proper diagnosis and treatment.