This repository is an web application to help a medical clinic with their day-to-day managment. It gives the possibility for a patient to make an appointment & view his documents (bills, prescriptions, ultrasound-images.etc). It also helps the doctors both with their schedules and diagnosis. Finally, it presents dashboards giving the admins insights about different & important aspects of managment.
It was made with love and Django~=3.1.
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Clone the project :
git clone https://github.com/deadly-panda/clinicApp.git -
Go to the project directory
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Create a Virtual Environment :
python -m venv myVenv -
Activate the virtual environment :
source myVenv/bin/activate -
Install requirements :
pip install -r requirements.txt -
Migrate :
python3 manage.py migrate -
Run the project :
python3 manage.py runserver -
You can also create a superuser to have admin permissions :
python3 manage.py createsuperuser
The image below shows the classes, in this case (Django case) the models, used in this web application. One should mention the use of django-allauth, an integrated set of Django applications addressing authentication, registration, account management.
The models
The patients can easly send an appointment request with the day & time they prefer & also the speciality of the doctor(general medecine, Ophthalmology..), view their prescriptions, bills & pay them, and most importantly have 24/7 access to their documents like x-ray shots or ultrasound images.
The appointment request is pending : waiting for a doctor to confirm or cancel.
Patient's documents
Patient's bills
The doctors recieve view their schedules, appointments requests & decide wether to accept or decline, a notifications is then sent to the patient asking for the appointment. In addition they can manage their patients information, add prescriptions, bills & important documents. The web application not only help with basic managment of the doctors schedules, but also helps with diagnosis. For now, it can help predict weather a patient might have a cardiovascular diseas from relational data like age, sexe & cholesterol level, Also, classify chest x-ray images as images with pneumonia or not. Other machine learning & deep learning models could be easly integrated with the web application.
Appointment request
Patient information & documents from the doctors side
The empty calendar
Admins have total access to the web application and all the information, they can add, modify or archive any entity like doctors, nurses, patients, prescriptions..etc. They also have a simple yet elegant dashboard, giving them insight about diffrent aspects like the ratio of paid/unpaid bills, appointments state distribution, patient sex distribution also information about insurrance companies & accounts..etc.
