Diagno-AI: Disease Prediction Application

Diagno-AI is a Streamlit-based web application designed to predict the likelihood of various diseases using machine learning models. This application provides an easy-to-use interface for users to input relevant medical data and receive predictions for diseases such as Parkinson's Disease, Lung Cancer, Heart Disease, and Diabetes.

• link for the app Diagno-AI

Work Demo

Features

• Parkinson's Disease Prediction: Predicts the likelihood of Parkinson's Disease based on vocal frequency and amplitude features.
• Lung Cancer Prediction: Predicts the likelihood of Lung Cancer using personal, primary, and secondary symptom data.
• Heart Disease Prediction: Predicts the likelihood of Heart Disease using patient information, cholesterol levels, and exercise-related factors.
• Diabetes Prediction: Predicts the likelihood of Diabetes using patient demographics, blood test results, and lifestyle factors.
• Customizable Background: The app includes a visually appealing background with a semi-transparent overlay for better readability.
• Responsive Design: The app is designed to work seamlessly across devices.

Installation

1. Clone the repository:

   git clone https://github.com/Parneet-Sandhu/Diagno-AI.git
   cd Diagno-AI

2. Install the required dependencies:

   pip install -r requirements.txt

3. Ensure the following directory structure exists:

   Diagno-AI/
   ├── app.py
   ├── Models/
   │    ├── parkinsons_model.sav
   │    ├── lungs_disease_model.sav
   │    ├── heart_disease_model.sav
   │    └── diabetes_prediction_model.sav
   ├── assets/
   └── requirements.txt
   

4. Run the application:

   streamlit run app.py

Usage

1. Open the application in your browser.
2. Select a disease from the dropdown menu.
3. Fill in the required input fields based on the selected disease.
4. Click the Predict button to get the prediction result.
5. View the prediction result, which will indicate whether the patient is likely to have the disease or not.

Models Used

The application uses pre-trained machine learning models stored in the Models directory. These models are trained on relevant datasets for each disease:

• Parkinson's Disease: parkinsons_model.sav
• Lung Cancer: lungs_disease_model.sav
• Heart Disease: heart_disease_model.sav
• Diabetes: diabetes_prediction_model.sav

File Structure

• app.py: Main application file containing the Streamlit code.
• Models/: Directory containing pre-trained machine learning models.
• assets/: Directory containing static assets like the background image.
• requirements.txt: File listing all the Python dependencies required for the project.

Dependencies

The application requires the following Python libraries:

• streamlit
• pandas
• pickle
• base64
• os

Install all dependencies using:

pip install -r requirements.txt

Disclaimer

This application is a prototype and should not be used as a substitute for professional medical advice, diagnosis, or treatment. Always consult with a qualified healthcare provider for medical concerns.

License

This project is licensed under the MIT License.

Acknowledgments

• The machine learning models used in this application were trained on publicly available datasets.
• Special thanks to the Streamlit community for providing an excellent framework for building interactive web applications.