Natural Language Interface for Patients’ Electronic Health Records

Presentation slide deck can be found here.

Seq2SQL

Setup

Requires a GPU to run.

Dataset require

• MIMIC-SQL (public)
• MIMIC III (private due to HIPAA-compliance)

Run

• Training: python TREQS/main.py

• Validate: python TREQS/main.py --task validate

• Test: python TREQS/main.py --task test

Natural Language Generation

For this portion of our project, we used RosaeNLG, an open-source (MIT) Natural Language Generation (NLG) library written in JavaScript, based on the Pug template engine. RosaeNLG is the first open-source NLG library which is easy to use and complete enough to write real life NLG applications. It can be run both server side (node.js) and client side, in a browser.

Setup

cd /natural-language-generation/
npm install

Run

npx rosaenlg-cli -l lang -w <template_filepath>
ex: npx rosaenlg-cli -l en_US -w templates_malesmokers/male_smokers_over45.pug

Patient Browser

Code for Patient Browser taken from: https://github.com/smart-on-fhir/patient-browser

Setup

cd /patient-browser-master/
npm install

Run

cd /patient-browser-master/build
npm start