It was really very difficult with the team to agree on what to build which are in line with a solution to a real-life problem. It was a task to agree on altogether, but the one thing which we can agree on that this Covid-19 have really changed our thinking about the front-line workers and we as the team wanted to solve a problem for them and help out society in whichever way possible.

Hence building a product which helps the Medical Organization in the logistics of the product in the supply chain part and also built a project for the relationship enrichment of the doctor-patient relationship, because of heavy schedule doctor cannot provide full attention to their patient, we wanted to touch base on that issue.

What it does

Helps doctors and medical organization to make sense of the data points which are readily available and try to visualize them in a better and interactive way which will help the institutes in better decision making for the current as near-future situation.

The supply chain part of the project help the institutes to get a look of the patient's cases which were predicted using TensorFlow libraries and with that, we help them to analyze which medical equipment they need and in which amount ( when compared to the present inventory ) a smart recommendation is shown on the dashboard and if the supplies are needed the interactive world map comes into place where they can see different manufactures, distributors and suppliers of that medical equipment.

We thought the above use case would be very useful for the Covid-19 Vaccine distribution in painting the logistics part in a healthy state ( reducing 1 problem for frontline workers, making 1 worry less for them). While to improve the doctor-patient relationship we have integrated a chatbot for the patient which act as a virtual assistant for the patient and directly connects with the doctor dashboard and making them know what the scenario of the patent is.

The Chatbot was built using TensorFlow and indeed can help the patient in answering some questions and doubts they might have during the course of medical treatment.

How We built it

The hack as a whole was divided into 4 phases i.e Design + Brainstorming, Phase-1 Development, Phase-2 Development, Buffer + Debugging with each phase having a teammate specific role and working on a crucial part of the project.

Design + Brainstorming: The first few days almost took us to come up with the idea ( after reading various reports and what the need is in the medical healthcare). It was also the phase when the designing of the product was done using Figma and basic prototyping was also done so that the development could be done.

Phase-1 Development: It was the initial development of the project including working on Zeplin for the frontend while parallelly making the database on the mysql and another team mate working on the chatbot.

Phase-2 Development: days later the front is done and the database almost 80% completed now comes the part to integrate the backend and bring the project to life. This phase we also took some workshops and contacted mentors whenever needed.

Buffer + Debugging: Each project cannot be fully completed on time (as usual ) and this was also not an outlier. After the setting, up and connecting now comes the part to host the project so that the other hackers can also see and give feedback which feature do they like and get some feedback from some other people.

Challenges We ran into

  1. Never ever we have used Zeplin but using it for the first time was challenging as well as a learning curve for us which helped us almost a couple of hours with the pre-built CSS code.
  2. Never used Tensorflow, it was a lot of googling and a lot of coffee to built it all together.
  3. Creating a chatbot was an experience and it was a lot of reading ( maybe more than we did this whole semester in college )
  4. We realized Tensorflow libraries do not host on Heroku and we have to pivot at a crucial stage.

Accomplishments that I'm proud of

  1. Making the design for the very first time was a great learning curve.
  2. Using the Tensorflow libraries helped us to hassle with many code pre hand

What We learned

  1. How to Design and Prototype a project in Figma
  2. How to make a website using bootstrap
  3. How to use Tensorflow in project
  4. The use of chatbot and integrating with our project
  5. How to deploy a project on a live server

What's next for Med-Chain

  1. Integrating with different API of Dr.Chrono to make it platform agnostics
  2. Make our Model more accurate to make the data visualization froemdly and easy to undretanbd
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