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.

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