When a medical emergency strikes, time is critical, and every decision could be a matter of life or death. aims to assist in this hectic time by calculating the optimum treatment location for its users.

What it does calculates a personalized treatment success rate at all hospitals near the user, and recommends the hospital which is best suited to treating the user's specific medical ailment.

How we built it is deployed on an asynchronous, RESTful web service built from scratch with Flask and Google gPRC. The AI powering is a custom neural network built with Google Tensorflow. It was trained on the John Snow Labs Hospital Comparison Database in the cloud via Amazon Web Services.

Challenges we ran into

Learning Tensorflow

Accomplishments that we're proud of

Learned Tensorflow

What's next for

We hope to implement a feedback loop for our users so that they can help the AI learn and improve. Additionally, we are exploring ways that we can deploy live after Hophacks to make it free and available to everyone.

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