Medicwise

Medicwise

Medicwise is a online doctor consultation website that facilitates chat, video calls and gesture-based video calls for handicapped-people solving one of the UN's Sustainable Development Goals.

The problem Medicwise solves

Why Medicwise?

We intend to stay at home due to the pandemic, and people are doubtful about going out to consult doctors nowadays.

  • People are opting for online personal health care. But there are various limitations to them.
    - The high brokerage of the platforms.
    - No direct interaction with the doctor until the patient pays high fees.
    - There is no support for handicapped people.
    - There are no healthcare coverage in rural/remote areas.
  • As a result, we developed a personal care web app that allows patients to consult doctors from the comfort of their own homes.
  • There are over a million deaf & dumb people. There is over 75 percent of people uneducated & need support. (according to the United Nation's 2021 report)
  • So we devised Medicwise as a solution to this problem so that it is accessible to everyone, regardless of their disabilities, to consult a doctor online.

What is Medicwise?

Medicwise is a facilitator that supports chats, video calls, and gesture calls along with an easy-to-use interface with integrated authentication and a scalable payment gateway.

  • There is a separate Admin Portal dedicated for the doctors.
  • Each portion of the Medicwise will have its own Room ID, given to patients by the respective doctors they want to consult.
  • Each doctor will have their own medic code so that patients can appoint them.
  • There is a chat room where you can communicate with your doctor.
  • There is a video room where you may communicate with your doctor via video call.
  • Lastly, there is a gesture room where mute and uneducated people can communicate with doctors using sign language.
    If the doctor doesn't understand sign language, we have machine learning models implemented using tensorflow that can decode sign language into text.
  • The patient authentication is facilitated with Auth0 Authentication. (with custom Email/Password or Google)
  • The payments facilitated by Stripe.

Challenges we ran into

Some of the major challenges that we tackled are,

  • When we were working with SocketIO to create chat rooms, it was giving CORS error. We enabled CORS by referring to the stack overflow answers using the following code snippet.

    const io = new Server(server, { cors: { origin: "*", methods: ["GET", "POST"], }, });

  • We have to train a Machine Learning model using Tensorflowjs which was quite difficult as we have previously worked with ML and Python only.
  • The deployment of the server and client-end was challenging as we were working on deployment with Azure for the first time. (even with Continuous Integration/Continuous Deployment) Thanks to the documentation provided by Azure Community. Not only we tackled to deploy our application but we also drafted it on GitHub for others.
  • We were handling payments with Stripe. So, we have to learn in depth about it and how we can handle payments using Stripe in test-mode.
  • Documenting everything on GitHub was tiresome, but we are satisfied by the result it produced.

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