An AI-powered interactive web application built with Streamlit that predicts whether a person is diabetic based on key medical parameters.
The model is trained on the PIMA Indians Diabetes Dataset using Scikit-learn.
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- Enter medical details through a user-friendly input form.
- Model predicts diabetes risk instantly.
- Trained on the PIMA Diabetes Dataset (Kaggle).
- Clean and interactive Streamlit interface.
- Sidebar navigation with developer details and links.
- Open the app in your browser.
- Enter the required medical information:
- Pregnancies
- Glucose Level
- Blood Pressure
- Skin Thickness
- Insulin Level
- BMI (Body Mass Index)
- Diabetes Pedigree Function
- Age
- Click Predict.
- Get results instantly:
- ✅ The person is not diabetic
- ❌ The person is diabetic
- Dataset Name: PIMA Indians Diabetes Database
- Source: Kaggle Dataset
- Attributes: 8 health parameters + outcome label
- Goal: Predict diabetes risk from health features
- Python 3.9+
- Streamlit (Web App UI)
- Scikit-learn (Machine Learning Model)
- NumPy & Pandas (Data Processing)
- streamlit-option-menu (UI Navigation)
Mirza Yasir Abdullah Baig
This project is for educational purposes only.
It should not be used as a substitute for professional medical advice or diagnosis.