DiagnoWeb is a web-based disease prediction application that utilizes machine learning models to provide accurate predictions based on user input. The project is built with Django, offering a user-friendly dashboard and secure authentication for a seamless experience.
- User Authentication: Secure user authentication to ensure data privacy.
- Dashboard: Intuitive dashboard for a user-friendly experience.
- Machine Learning Models:
- Decision Tree: A model for decision-making based on provided features.
- Naive Bayes: Utilizes probabilistic algorithms for prediction.
- Random Forest: Enhances accuracy through an ensemble of decision trees.
Clone the repository:
git clone https://github.com/yourusername/DiagnoWeb.git
cd DiagnoWeb- Create an account or log in using the provided authentication system.
- Navigate to the dashboard and enter the relevant features for disease prediction.
- Receive accurate predictions from the deployed machine learning models.
The machine learning models were trained on a comprehensive dataset to ensure accurate predictions. The decision tree, naive Bayes, and random forest models collectively contribute to the robustness of DiagnoWeb.
Contributions are welcome! If you have suggestions or would like to improve DiagnoWeb, feel free to open an issue or submit a pull request.
This project is licensed under the MIT License.