The COVID-19 track caught my eye when I first came to the hack3 website, and I've been spending most of my time at home due to quarantine. I've had some experience with image classification in the past, so I thought, why not?

What it does

The model I've implemented is meant to categorize provided images as either positive or negative for patients.

How I built it

I built it using a custom PyTorch model with a cross-entropy loss function and SGD optimizer.

Challenges I ran into

Tuning hyperparameters to produce the best validation loss, as well as combining datasets.

Accomplishments that I'm proud of

The 44% test accuracy the model attained.

What I learned

That hackathons are little bit nerve-wracking.

What's next for COVID-19 Detector from X-Rays

Fixing the image classification and getting a larger dataset.

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