“Neural Covidex can provide an easier way for clinicians, researchers, and other experts to navigate the plethora of information that is emerging from the scientific community and obtain relevant, actionable evidence as quickly as possible,” said Lin, who holds the David R. Cheriton Chair in the David R. Cheriton School of Computer Science.

Lin, like many others, wanted to contribute in whatever way he could in the fight against COVID-19, says a press release. His research focuses on building systems that help users gain insights from large amounts of text, leveraging techniques based on artificial intelligence (AI) and neural networks. He was able to rapidly redirect his research into building natural language processing and information retrieval components for exploring Allen Institute for AI’s dataset.

CORD-19 consists of articles dating back to SARS and MERS and previous coronaviruses. It includes knowledge on a wide range of topics, spanning public health, clinical care, epidemiology, genetics, and more. The dataset is updated weekly as new research is published in peer-reviewed publications and various preprint services.

“The ultimate goal of our work is to build a system that can help experts who are working on this worldwide pandemic,” said Lin. “For example, doctors who are conducting meta-analyses to update clinical care guidelines and virologists who are working on developing a vaccine. We know we’re still pretty far from this, but we’re working hard to improve our system incrementally by leveraging the latest AI techniques.”

Working with Lin is his colleague professor Kyunghyun Cho of New York University and two Waterloo undergraduate students in Computer Science, Edwin Zhang and Nikhil Gupta.