The inspiration for this project was originated from a vision of what a post-COVID 19 world should encompass. the team asked ourselves what the future of tech looked liked for healthcare, and how there lacked a comprehensive online healthcare service. In the 21st century, when our cellphones are more powerful than the Apollo missions that landed on the moon, a disruption in the healthcare system was the next revolutionary idea that inspired our team.

What it does

Evexia is a healthcare app that includes AI incorporated with a comprehensive interface in order to provide healthcare online. It allows for patients to set up calls with healthcare professionals, monitor their prescriptions, access their record and also self diagnose. There is a neural network that is trained on a plethora of diseases and medical expertise, which basically is an automated healthcare provider. For physical check ups, the app provides a geolocation of nearby hospitals for ease of access.

How I built it

The original chatbot is built with a trained neural network using python. The chatbot used in the website is embedded and configured to match the python based chatbot.

The website is built with html, css and javascript, and the chatbot is a javascript plugin.

The app interface is built using react native.

The video was recorded by using a program called Rotato.

Challenges I ran into

For creating an automated chatbot, running the python script and training the neural network took a lot of planning. The neural network required the correct input parameters, and -of course- debugging.

Also, embedding a chatbot like interface into an html website was challenging, since chatbots require a comprehensive javascript environment, with a python backend. It would take a firebase database to send messages between the python database and the user. The engineers decided, in the interest of time, that it was better to take a pre-built chatbot environment and embed it into the website. The configuration of the automated chatbot was made to match the python based chatbot, and would give the same responses.

Rendering of the video took 33 GBs+ of memory, and overclocked the CPU.

Accomplishments that I'm proud of

The team is proud of the overall comprehensiveness of the application built and the solution provided. The implications of the idea, providing easy access to healthcare, instills in the team a belief that ideas are powerful.

Another source of pride is the overall presentation itself. It provides readers with a solid understanding of the vision behind Evexia in a simple, yet aesthetic manner.

What I learned

We learned a massive amount about the field of medicine, and about data science through our extensive search for medical records as well as medical scans and imagery. The organization of the data into a proper structure using the Google servers helped us understand system architecture better.

The team learned that a conscious effort in the right direction is able to bring about solid innovations. The team was deliberate in everything we did, every feature, every click, every single question we asked ourselves was directed at building a meaningful product.

What's next for Evexia

The team wants to pursue making Evexia the face of healthcare in the digital economy. To do this, we need access to even more medical records which will allow us to keep training the model with more data to increase the accuracy of the results. We must consult healthcare specialists and get their take on what is needed to improve the relationship of healthcare workers and patients, especially on the online platform where human connection is limited. If we can ensure that people everywhere, regardless of social class, in any situation, can have access to affordable healthcare at their fingertips, then we have surely accomplished our goal. registration - ( Health at your Fingertips)

Share this project: