As we can tell by an enormously growing infection rate, it's important that we diagnose potential symptoms of COVID-19 and communicate with our local health departments.
What it does
Trachio is a web app that allows you to upload spectrograms of a patient’s lung sounds in order to diagnose and report potential symptoms of COVID-19 to one’s local health department.
How I built it
I created a Flask backend that communicates with a dynamic HTML/CSS frontend, which allows you to upload audio spectrograms. A classification is made through the Google AutoML Vision API and returned to display potential symptoms on the frontend. There is also a feature that allows you to quickly contact local health authorities via email, which is plain HTML.
Challenges I ran into
Of course, getting Google Cloud authentication to work properly was a hassle. Also, I was a bit slow to develop because I had never used Flask before.
Accomplishments that I'm proud of
But regardless, I'm really proud of how many tools I learned to use in the past 24 hours. I dared myself to go solo and I feel like it paid off for my own learning.
What I learned
Basically the entirety of Flask, and servers in general.
What's next for Trachio
Improve the model's accuracy, and make the frontend prettier.