[lekanwang]

As a healthcare tech investor, I do see a lot of startups selling potentially dangerous AI systems into the healthcare system. That said, there are also a good number of companies that are implementing systems thoughtfully to address a number of issues that are very real in healthcare like staff burnout, continuing education, adherence to standard of care, managing complex value-based payment contracts and coordination of care, etc. The trouble I see is that clinician/hospital buyers of these systems can't always tell the difference. A basic initial filter that can be used is simply (a) does the team have an experienced medical professional with power on its executive team, and (b) does the team credibly know how to measure clinical quality impact of what they're building and do they have a plan to honestly measure it.

[ebiester]

Where do you see it being added thoughtfully?

[xattt]

Fall prevention to start. This is relatively benign and a good place for health staff to gain comfort around the technology.

Many nurses already have an internal sense when a model might be “off” for a patient, so it’s easier to know when it’s predicting accurately or not.

(1) https://www.frontiersin.org/articles/10.3389/fmed.2023.12851...

[peteradio]

Oh it just so happens to be his portfolio.

[pc86]

Is it good because it's in his portfolio, or is it in his portfolio because it's good?