QnQ

This project develops a tool to predict and recommend ADHD medications, aiming to quickly find the right fit by anticipating individual reactions to reduce trial and error.

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Inspiration

Medicating ADHD is often a tedious and lengthy journey towards finding the right drug fit for an individual. This is often due to the unwanted side effects that come along with these medications. The idea behind this project is to come up with a tool that alleviates part of this tedium by predicting which reactions an individual will most likely have to certain drugs and recommending others. With the goal being for individuals to find their right medication fit much faster due to these recommendations.

What it does

Uses rule based decision tree to predict ADHD drug recommendations through answers from a questionnaire.

How we built it

Using React.js and Node.js

Challenges we ran into

We originally wanted to use phenotypes and gene variants along with more advanced ML techniques to predict drug reactions, however, this proved to be too much for the given time window.

Accomplishments that we're proud of

Finishing a version of it that still works fairly well despite having to shift from our original idea deep into the day.

What we learned

More about genetics, ADHD, project collaboration, conflict resolution

What's next for QnQ

Finish our original project idea with gene variants and phenotypes.

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