The Mayo Clinic embeds its engineers in real patient treatment

The interaction between statistical methods (algorithms and data analysis) and actual work is critical and fairly obviously important. But articles like this show how it is still something we need to focus on.

My father, William Hunter, and George Box worked on these ideas and applied statistics decades ago.

Related: Two resources, largely untapped in American organizations, are potential information and employee creativity. https://williamghunter.net/articles/managing_our_way_to_econ...

The Scientific Context of Quality Improvement

https://williamghunter.net/george-box-articles/the-scientifi...

Good article. Shows the risks/difficulty in applying machine learning models in the wild. Also shows the more sober side of applying ML models, where a domain expert says "Yeah, I know, I didn't need an ML model to tell me that". ML models will make mistakes based on bias, but hopefully in the long run they will outperform humans.

What a weird headline. The “acid test” is that the AI must actually help patients. I don’t mean to be flippant, but that seems pretty obvious.

Most of the article is the way that the Mayo Clinic embeds its engineers in real patient treatment. That’s actually interesting.

I agree with this approach for software devs in any business. One of the cool things one of my employers (a manufacturing company) did was send me out for a day to a plant and have me see how everything worked. It made some of the websites I was building for our plant workers much easier when I already had a good idea of what they needed it for.

If you're not focused on the patients right from the beginning, you have already failed.

It’s going to take a long time for the “AI” hype cycle to fully run its course. Expect many more of these articles.