c2-labs / c2labs-ornl-challenge

Smoky Mountains Data Challenge - Sponsored by ORNL

C2 Labs participated in this data challenge to demonstrate our growing capabilities in big data and data science. Information about the challenge can be found on the Smoky Mountain Data Challenge website.

We chose to participate in Challenge 6 - Using Artificial Intelligence Techniques to Match Patients with their Best Clinical Trial Options.

About this Repository

There were multiple components of this project that were assembled to deliver the final solution:

• ElasticSearch - configured an ELK stack to provide a big data platform for effeciently searching through large amounts of data leveraging Azure Kubernetes Service.
• Datasets - scripts for processing data sets and flat files created from data engineering work
• Python - contains analytical techniques using Python to build a data science model for matching patients to trials
• R - contains analytical techniques using R to build a data science model for matching patients to trials
• Data Wookies - contains source code for the Angular application that provides a front-end for interacting with the data models and APIs for processing data and connecting to ElasticSearch

Solution Architecture

Scale-Out Architecture

Run the Application Locally

• Install NodeJS, Angular, and Python3 on your local development machine
• Install all dependencies with npm install and pip install
• From the data-wookies folder, run npm run dev to start the Node.js web server for Express (hosts the APIs)
• From the data-wookies\client folder, run ng serve to start the Angular web server (front-end application)

Pre-Requisites

• Download and install Python (recommend version 3) - Download
• Download and install NodeJS (recommend 12.18.3 Long Term Support) - Download
• Download and install Angular CLI (must be >= 9.0 version) - Download
• Install the application packages for Python using pip, python3 -m pip install packageName

Development server

Open a terminal and from the datawookies folder run npm run dev to startup the NodeJS dev server.

Open a second terminal and from the client folder run ng serve to startup the Angular dev server. Open the website locally

The app will automatically reload if you change any of the Angualr source files. Restart the NodeJS server if you change any Python or Express.js code.

Code scaffolding

Run ng generate component component-name to generate a new component. You can also use ng generate directive|pipe|service|class|guard|interface|enum|module.

Build

Run ng build to build the project. The build artifacts will be stored in the dist/ directory. Use the --prod flag for a production build.

Running unit tests

Run ng test to execute the unit tests via Karma.

Running end-to-end tests

Run ng e2e to execute the end-to-end tests via Protractor.

Further help

To get more help on the Angular CLI use ng help or go check out the Angular CLI README.