App which serves as an informative resource on diseases and also fosters a data-driven approach to healthcare.
This data visualization project serves as a platform for understanding diseases by providing in-depth insights into their symptoms, precautions and associated data. Leveraging advanced visualization techniques, the project presents a user-friendly interface with interactive dashboards that allow users to explore a vast array of health conditions. One key aspect of the project is its emphasis on accessibility and user engagement. Through dynamic charts, graphs, and infographics, complex medical information is transformed into easily understandable visuals. This approach encourages users, ranging from healthcare professionals to the general public, to engage with and comprehend the nuances of various diseases.
Set up locally
Prequisites: Ensure you have pycharm and python installed on your machine. You can download them from https://www.jetbrains.com/pycharm/download and https://www.python.org/ respectively
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Preparation:
• Ensure Python 3.x is installed. If not, install Python from python.org.
• Download or clone the project repository from GitHub.
gh repo clone SohaSk/Disease-visualizer
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Installation Process:
• Open a terminal and navigate to the project directory.
• Install Django and required dependencies using pip:
pip install -r requirements.txt.
• Verify installed packages with: pip list.
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Setup and Configuration:
• Create a Django project:
django-admin startproject DiseasesInfo.
• Create a Django app for disease data:
python manage.py startapp App.
• Configure database settings in settings.py with your chosen database system.
• Design and implement models for disease data in the app's models.py.
• Implement views, templates, and URL configurations for disease information display and data visualization.
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Testing:
• Navigate to the project directory containing manage.py
cd ./DiseasesInfo/
• Start the Django development server:
python manage.py runserver.
• Access the website via a browser at http://127.0.0.1:8000/ and test disease information pages.
• Validate data visualization functionality and interactions.
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Troubleshooting:
• Common issues: database connection errors, dependencies mismatch.
• Refer to Django's official documentation for solutions.
• Check console logs and Django's error handling for debugging assistance.
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Post-Installation Steps:
• Set up admin access to manage disease data via the Django admin panel.
• Implement user authentication, if required.
• Optimize visualization features for better user experience.
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Documentation Updates:
• Encourage user feedback and contributions via the project's GitHub repository.
• Regularly update documentation with troubleshooting tips and improvements.
• Detailed tutorials and documentation on Django can be found at Django's official documentation.
• Provide specific instructions and examples for data visualization implementation using Django templates and chosen visualization libraries.
This project was initiated and developed by members of the Milestone Club at VIT AP University. Our club is dedicated to fostering innovation, collaboration, and learning among students interested in technology and software development.
The Milestone Club at VIT AP University is a student-driven organization aimed at providing a platform for students to explore and develop their skills in various technological domains. We focus on organizing collaborative projects to enhance practical knowledge and encourage innovation.
We extend our gratitude to the contributors and members of the Milestone Club who participated in the development of this project. Their dedication and efforts have been instrumental in bringing this project to fruition.
For updates, events, and highlights from the Milestone Club, follow us on Instagram.
Please read our Contribution Guidelines before contributing to this project.
This project is licensed under the MIT License - see the LICENSE file for details.