Welcome to the Diabetes Risk Prediction for Females web app repository! This project aims to assist in identifying diabetes risk for females through an intuitive and interactive interface. The model behind this application is the reliable AdaBoost Classifier.
📍 Diabetes Dataset Kaggle
- 🎛️ Interactive Input Sliders: Users can easily input their health data using sliders.
- 🖥️ Web-Based Application: Powered by Streamlit for a seamless experience.
- 📊 Accurate Predictions: Utilizes the AdaBoost Classifier for dependable results.
- 🔍 Insightful Results: Categorizes predictions into three risk levels for better understanding.
- Python: Core programming language.
- Streamlit: Framework for creating interactive web apps.
- AdaBoost Classifier: Machine learning model for predictions.
- NumPy: For numerical computations.
Below are the types of outputs you can expect from the app:
| Risk Level | Prediction | Example Input |
|---|---|---|
| 1️⃣ Normal Risk | Not very probable you will get diabetes soon. Take care of your health! | Pregnancies: 0, Glucose: 80, Blood Pressure: 70, Skin Thickness: 20, Insulin: 15, BMI: 22.5, DPF: 0.3, Age: 25 |
| 2️⃣ Moderate Risk | It is probable you might develop diabetes soon. Please consult a healthcare professional. | Pregnancies: 2, Glucose: 140, Blood Pressure: 85, Skin Thickness: 30, Insulin: 90, BMI: 27.5, DPF: 0.8, Age: 35 |
| 3️⃣ High Risk | It is highly probable you might develop diabetes. Immediate medical consultation is recommended. | Pregnancies: 6, Glucose: 180, Blood Pressure: 100, Skin Thickness: 45, Insulin: 120, BMI: 35.0, DPF: 1.2, Age: 50 |
Here are the visual representations of the outputs:
Normal Risk |
Moderate Risk |
High Risk |
Thank you for visiting this project! 🚀