Inspiration

Make it easier to find scientific information about covid-19 from a reliable source. This project aims to provide a visual way to browse through the papers related to the different coronaviruses.

What it does

In addition to our browser which helps you find scientifc papers, we use state-of-the-art methods in NLP to find papers which are related.

We also used NLP tools to classify each paper with a topic and a subtopic, and we then built a network of the papers in each subtopic. These networks helps the user to quickly get a visual idea of the existing papers in a field of research, and to see how close they are.

On top of that, we want to have a search engine that will allow researchers to see about which topic and subtopic the queried papers are, and where they are located withing the network of papers of the subtopic.

Our search engine is not completely linked to our visualization tool yet, but that will come soon.

Disclaimer: some of the work was already done before the start of the Lauzhack hackathon (this project started a week before for the CodeVsCovid19 hackathon).

How it was built

Python back end with deep learning for NLP with javascript front end for great user usability.

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