The problem Virtual Hospital solves

The project makes an attempt to bring online all the services provided by the Hospitals. We have made a platform where the patients and the Doctors can register themselves. The patient can log in to his profile to make a request for an appointment to any registered Doctor. As soon as the Doctor Logs in , he will get the list of appointments on his Dashboard. The Doctor can right away make a video call to patient. We have made a status tag for every appointment. The status is yellow as long as the Doctor does not gives the feedback (list of required medicines and checkups) and it becomes green once the Doctor's feedback is returned. The Feedback from the Doctor will be displayed on the patient's profile along with the appointment's history.

We have provided more features to assist and facilitate the Doctor as well as the patient. The Doctor will be given an option to send the list of checkups and medicines which patients needs to get done. The Doctor will also be given an option to reappoint the patient after a given time. The patient on the other hand will be given an option to upload the images of the reports of the test and scans which were asked by the Doctor. These reports will be displayed to the doctor along with the appointment request. We have added a Deep Learning model at an intermediate layer between the patient and the Doctor. The model will be used to do Analysis on the reports/scans uploaded by the patients the model will predict the contingencies and in case of any severe disease it will alert the doctor through the mail.

Challenges we ran into

We faced some severe challenges while deploying the project as initially it was challenging to deploy Auth0 middleware for authentication on azure cloud. It was difficult to find the Data to train the Deep Learning model which we have hosted on Azure cloud. Auth0 was new for our team so we took time to cope up with it. Uploading caused error initially.
We came over each nd every error by vigorous tries. We read and understood the documentation of Auth0 to overcome all errors arising due to it. For Deep Learning model we finally found data on Kagle and implemented using Azure Cognitive Services Computer Vision API.