"The NLOS that spits out the Transplant Benefit Scores is one of dozens of algorithms in use in healthcare systems around the world. These applied statistical systems are used by physicians and hospitals to aid decisions such as who receives heart surgery and organ transplantation, which patients are at the highest risk of surgical complications, and in diagnosing cancers and brain injury. The intent behind predictive algorithms, like the NLOS, is to make consequential decisions fairer."
https://www.ft.com/content/5125c83a-b82b-40c5-8b35-99579e087951
@cyrilpedia can't read the article as it is paywalled... I guess the conclusion is that they are not necessarily making things fairer?
@nicolaromano Depends - the UK liver transplantation algo they focus more on in this piece seems to be a good attempt at improving a difficult situation. But as they say here, there is a fundamental problem:
'Because there aren’t enough livers for all 700 people on the UK’s list, “transplantation remains a zero-sum game and any adjustment in allocation is simply a case of causing harm to one to help another,” wrote Raj Prasad, a surgeon at Leeds Teaching Hospitals, in the Lancet this year.'
@nicolaromano They describe briefly US cases, and then it is just a disaster, because of course the money dimension takes over.