Inspiration: People often have worries about their health but do not know if their symptoms warrant a trip to the doctor.
What it does: Pill Papa accepts up to 26 symptoms from the patient/user and returns them their likely ailment/condition with high accuracy.
How we built it: We took a CSV and put it into the decision tree classifier. Then, we tested how well that classifier was. After that, we took the data inputted into the front end and gave it to the classifier to make a prediction as to what field that ailment was in. We took the output and put it on the frontend.
Challenges we ran into: Our main challenge was syncing the UI and the backend code as they were developed on different platforms using different languages.
Accomplishments that we're proud of: We are proud of the fact that our team was able to collaborate together to create an app of this complexity given the many challenges it presented, especially since this app can impact people's lives in a positive way.
What we learned: The use of computer science can help benefit people's lives in a variety of ways, even in fields like healthcare.
What's next for Pill Papa: In the future, we would like to implement a feature that assesses the severity of the symptoms and we would also like to seek FDA endorsement so we can legally prescribe medicines and provide medical recommendations.
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