This repo originated as a part of a hackathon sponsored by Wei Shung Chung, and he created the stub data access code. Thanks to him for taking the initiative to get some data geeks going.
There are 2 summary videos you can watch about this too: Short version:https://www.youtube.com/watch?v=lLJR3ItY938
Long (statistical) version: https://www.youtube.com/watch?v=WjBVeD-_I-A
This analysis code is described in this presentation: https://docs.google.com/presentation/d/1kIeD-NMUM554xr3uRPVTRH7SidZ2B7bgXLWpCiyDMXI/edit?usp=sharing
It is designed front-to-back to run in a Colab Jupyter notebook and updates with a very few changes (mostly to the dates of analysis).
We've done our best to document the data sets, methodology, assumptions and known caveats (most specifically the variance created by the lack of testing data).
- World Health Organization (WHO) Advice for Public
- CDC Coronavirus Disease 2019 (COVID-19) Situation Summary
- World Health Organization (WHO)
- WHO on LinkedIn
- HealthMap
- Coronavirus COVID-19 Global Cases by Johns Hopkins CSSE
- Centers of Disease Control and Prevention (CDC)
- Singapore Covid-19 Dashboard
- The New England Journal of Medicine
- The Lancent: Infectious Diseases
- JAMA Network: Covid-19 Collection
- Chinese Hospitals Deploy AI to Help Diagnose Covid-19
- COVID-19 and artificial intelligence: protecting health-care workers and curbing the spread
- Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases
- Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR
- Alibaba develops AI system for Covid-19 diagnosis
If you want to work on other AI-related projects to improve mankind, email Wei Shung Chung at ai.for.mankind@gmail.com