literature.md

2nd Covid-19 Online Hackathon: Mining Medical Literature using AI

Kaggle: COVID-19 Open Research Dataset Challenge

A COVID-19 Open Research Dataset in a machine readable format was released which contains 29,000 scientific articles published in journals and on preprint servers to invite experts use AI to discover new insights abaout the virus, its behavior, or possible treatments.

https://www.whitehouse.gov/briefings-statements/call-action-tech-community-new-machine-readable-covid-19-dataset/

Join Slack Channel for Discussion

• AI For Mankind Slack Channel

Kaggle Tasks

https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge/tasks

Example Tasks:

1. What is known about transmission, incubation, and environmental stability?
2. What do we know about COVID-19 risk factors?
3. What do we know about vaccines and therapeutics?
4. What has been published about medical care?

Notebooks

https://www.kaggle.com/tarunpaparaju/covid-19-dataset-gaining-actionable-insights

Resources

• The Science Behind the Coronavirus
• A complete tutorial for Named Entity Recognition and Extraction in Natural Language Processing using Neural Nets
• Complete Tutorial on Named Entity Recognition (NER) using Python and Keras
• National Center for Biotechnology Information: BioNLP Research

Papers

• BioBERT: a pre-trained biomedical language representation model for biomedical text mining
• A text-mining approach to obtain detailed treatment information from free-text fields in population-based cancer registries: A study of non-small cell lung cancer in California