How to test
Currently the frontend webpage for this project isn't fully implemented yet. In order to achieve a working prediction you must submit your data following the example_post file. To submit the data to the algorithm through this project type curl -X POST localhost:5000/submit_data -d @example_post while the project is running.
The goal
The goal of the frontend project is to provide an easy method for doctors around the world to utilize UC Davis data to diagnose leptospirosis.
What will it look like?
The result will be a simple and easy to use front-end webpage that anyone in the world can use to easily input required patient data and blood work in order to be run by the algorithm.
What does it need to do?
- Allow the user to easily upload bloodwork data and patient data
- Parse incoming patient data from the PDF file
- Run the lepto-classifier machine learning model on the data
- Return the result to the user
- Save the data to a database for further analysis and for iteration on the ML model
- Provide an easy method for retrieving data from the database in the future (Similar to cardinal)
Please take a look at the full document outlining this project here