In this ninth episode, we discuss the analysis of COVID-19 testing and surveillance data with guest host Dr. Jeff Morris from the University of Pennsylvania who is the founder and author of the popular COVID-19 Data Science blog. We also discuss several high-profile papers retracted from the New England Journal of Medicine and The Lancet for possible data fraud. Finally, we discuss different philosophical approaches to running a research lab. We include our usual news and items of interest.

The COVID-19 Data Science Blog.

Piece by Carl Zimmer in the New York Times on how to read scientific papers.

Piece in Science on why some AI advances might not be real.

Are we really making much progress? A worrying analysis of recent neural recommendation approaches.

Blog post about misuse of machine learning benchmark data.

The retracted NEJM and Lancet papers.

Machine learning cheatsheets.

Piece in Nature about mathematicians boycotting work for police departments in response to police brutality and racism and the letter they wrote.

10 recommendations for supporting open pathogen genomic analysis in public health published in Nature Medicine.

7 tips for managing knowledge workers published in Science.