#Medical Sessions- Lets Analyse Patient Report data

Docker application to serve NLP insights of programme feedback for medical patients of an APP, including NER, Keyphrase extraction, theme detection and sentiment analysis Initially appeared on gist

These instructions will give you a copy of the project up and running on your local machine for development and testing purposes. This project has been tested on a localhost

First things first, clone the project to localhost and navigate to your commandline git clone https://github.com/cm2435/Medical-Session-Inferance-App/edit/main/README.md

Check that docker desktop daemon is running, navigate to command line and run docker-comopse up -d --build

This should start the program. Wait for a while, the backend transformers download API is slow. This needs a refactor

Go to http:https://localhost:8501/ And enjoy running!

Docker, for windows WSL and other Daemon requiremnts. Python >=3.6 Check backend and frontend requirements.txt for their respective dependancies.

TODO- Deploy to pypi so that App can be downloaded

python -m pip install Medical-Session-Inferance

TODO- Write the automated tests for check cases using numpy arrays other than examples TODO- Impliment pandas dataframes to fit and predict models

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

TODO- Impliment contributing.md

• **Charlie Masters ** - Currently Sole contributer - LinkedIn

Please feel free to fork and contribute to appear down Here!