ezmeds

Inspiration

What it does

Our application aims to streamline the telemedicine process. Users are able to learn of safe and reasonable remedies for their symptoms, receive mental health tips and resources, or find pharmacies and doctors who can provide aid as well.

How we built it

This application was built using the MIT App Inventor. We collaborated by exporting the app as an AIA file. Whenever someone different worked on the app, they imported the most recent AIA file and exported it when they were finished.

Challenges we ran into

Our initial app idea was to use Streamlit for our own POC app rather than the MIT app inventor. However, due to our own time constraints for development, as everyone was busy, we evaluated that the time it would take our members new to development to familiarize themselves with both streamlit and version control was too long. As such, we defaulted to the MIT App Inventor. Our group also had many ideas for our app ideas but was hard-pressed to pick one. We eventually settled on Telemedicine after sitting down for a longer discussion. Moreover, we had trouble integrating a ChatBot into the app due to the financial constraints of hosting an OpenAI API.

Accomplishments that we're proud of

We are proud to have made an app with clear functionalities geared towards our own community. For example, we were able to implement an API of mental health resources in Tennessee into our app.

What we learned

Apps have the capability of impacting a large audience of people and making a difference in many people's lives. However, apps can also harm. In making our app, we quickly understood the importance of providing accurate and responsible medical feedback – it was important for us to create a good product that took medical help seriously.

What's next for ezmeds

Telemedicine is becoming far more personalized with the integration of biometric data and genomic-data in applications like CRISPR-Cas9. With these, the range of medications available to patients has expanded to an unimaginable scale. However, the range of error has equally multiplied. Far too many nuances exist with prescriptions, causing incorrect prognosis and potentially lethal mistakes in treatment. Therefore, the future holds a much-needed, drastic increase in specificity and personalization of medicine for our project. This is possible through Artificial Intelligence, which has the capability of learning each user’s needs and all of the inevitable nuances that separate one client from the next through constant algorithmic learning of a patient’s preferences, physiological limits and capabilities, allergies, etc. With this technology, our project can become safer and much more suited for the upcoming decades in medicine by ensuring that every client can have access to any medicine they need, tailor-made for their illness, at the tips of their fingers and in the reaches of their pockets.

Built With

• mit-app-inventor
• streamlit