In a previous article, I wrote about the importance (and challenges) of assessing an ML model’s UX/operational/commercial efficacy (i.e., impact when used under ideal/controlled circumstances) and effectiveness (i.e., impact in real-world conditions) as part of an ML product. In the same article, I discussed the similarities of this problem to the ones medical researchers deal with, when assessing the efficacy and effectiveness of candidate interventions (such as vaccines), and how ML products can draw parallels and transfer some such terms and learnings from the medical domain to theirs. This article will expand on that story.

First, I would like to…

Reza Khorshidi

Chief Scientist at AIG, and PI at University of Oxford’s Deep Medicine Program; interested in Machine Learning in Biomedicine and FinTech

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store