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This project uses diabetes dataset related to people (age, sex, bmi, ldl etc..) who have been given a value that corresponds to a certain progression of diabetes. A machine learning model was developed with a test set for evaluating model (30% testing \u0026 70% training) and then use to build this app. for every user inputs of (age, sex, bmi, ldl etc…) a prediction of a certain progression of diabetes can be made before having clinical trials.\n\n  Built with Django, Pandas, scikit-learn Bootstrap and Javascript.\n\n![EHealth](sample/sample1.png)\n![EHealth](sample/sample2.png)\n![EHealth](sample/sample3.png)\n![EHealth](sample/sample1.gif)\n![EHealth](sample/sample.gif)\n\n### App Features\n\n-   Machine learning prediction model for diabetes.\n-   Multiple custom user type Doctor/Patient.\n-   Patient can register, predict there Diabetes status, and build a medical history\n-   Admin can view Patient information and medical history.\n-   Patient can view, download results of diabetes \u0026 medical history recorded in PDF format.\n\n\n### How to Set up the application\nOpen terminal and use git clone command to download the remote Github repository to your computer\n```bash\n  1. git clone \n  2. cd e_health\n  3. python3 -m venv venv\n  4. venv/bin/activate\n  5. pip3 install -r requirements.txt\n  6. Generate a new secret key or use default\n  7. python manage.py makemigrations\n  8. python manage.py migrate\n  9. python manage.py createsuperuser\n  10. python manage.py runserver\n  11. visit live server at http://127.0.0.1:8000/","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjibril14%2Fe-health-django-machine-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjibril14%2Fe-health-django-machine-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjibril14%2Fe-health-django-machine-learning/lists"}