Inspiration
- We are inspired by the growing counterfeit pharmaceutical market, mainly in developing countries. We hope to increase safety and to give people the tools to make conscious and educated decisions about their health.
What it does
- Via our interface, the user will take a photo of the potentially malicious prescription bottle while in the pharmacy. The backend of the application will then use OCR and NLTK tools to convert this to a .txt file. We will then compare this .txt file to dataset of labels curated by the National Library of Medicine. The app will then output a "risk gradient", informing the consumer of possible inconsistencies between the label they have scanned and the official label on file. All user uploads will be stored and flagged if unsafe to expand the abilities and knowledge of the app.
How we built it
- Python (including PyTesseract, PySimpleGUI, and Python Imaging Library) provided the main basis for the project, which was enhanced by knowledge of our team members from past projects.
Challenges we ran into
- Due to the time constraints of the project, we were unable to link our outputted .txt file to the data base to return accurate or inaccurate comparisons of real bottles.
Accomplishments that we're proud of
- We are proud of identifying a large issue in the global market and implementing a new idea that may be able to help people, as well as our utilization of a variety of Python tools.
What we learned
- By being involved in this project as a group, we learned a lot about how large of an issue that counterfeit drugs are for so many people. Though unknown to many, the lack of health literacy and safety around the world is a a serious issue that we are interested in minimizing.
What's next for RealRx - The Shakes
- We hope to continue working on this project- our next steps are developing a working prototype, which includes code to compare the txt file from our NLTK to dataset images, working out the app's interface, and running tests to make sure the code works.
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