As AI capabilities advance in complex medical scenarios that doctors face on a daily basis, the technology remains controversial in medical communities.
I mean if the AI takes women seriously then that’s honestly already better than most of the doctors I’ve had
To allow ChatGPT or comparable AI models to be deployed in hospitals, Succi said that more benchmark research and regulatory guidance is needed, and diagnostic success rates need to rise to between 80% and 90%.
Sucks if your one of the 10-20% who don’t get proper treatment (maybe die?) because some doctor doesn’t have time to double check. But hey … efficiency!
Ya that’s a fundamental misunderstanding of percentages. For an analogous situation with which we’re all more intuitively familiar, a self driving car that is 99.9% accurate in detecting obstacles crashes into one in one thousand people and/or things. That sucks.
Also, most importantly, LLMs are incapable of collaboration, something very important in any complex human endeavor but difficult to measures, and therefore undervalued by our inane, metrics-driven business culture. Chatgpt won’t develop meaningful, mutually beneficial relationships with its colleagues, who can ask each other for their thoughts when they don’t understand something. It’ll just spout bullshit when it’s wrong, not because it doesn’t know, but because it has no concept of knowing at all.
It really needs to be pinned to the top of every single discussion around chatgbt:
It does not give answers because it knows. It gives answers because it thinks it looks right.
Remember back in school when you didn’t study for a test and went through picking answers that “looked right” because you vaguely remember hearing the words in Answer B during class at some point?
It will never have wisdom and intuition from experience, and that’s critically important for doctors.
A few things, that’s an abysmal rate when it comes to people’s health. A doctor with that success rate would be sued into next century. The rate dropped further when it came to differential diagnosis, implying chat gpt was leaving out important rarer possibilities. Often doctors work by starting with the most common and narrow down from there after repeated rounds of testing if it ends up being something uncommon, but one of their primary jobs is also thinking about rarer dangerous stuff that can mimic more common things and must be ruled out immediately.
Most importantly, the information fed into this was optimized with accurate descriptive medical terminology. This is a language that, in general, patients do not speak. People can also describe things very differently, for instance a patient saying something is weak when a doctor may say no that’s numb not weak or visa versa. And dizzy could mean just about anything. Someone typing their own story directly into chat gpt is going to get much worse results than this without someone to interpret the word choices and ask the right questions that people may not even realize are important.
Anyways, the possibilities of AI use in Healthcare is interesting, but disappointing it does worse the less common things get and is bad at a differential diagnosis, the areas that would be really helpful as an aid to diagnosis. Some other areas to think about though could be maybe as a front end to find clinical trials with the us gov database, which can be hard to browse, or maybe streamlining the endless insurance paperwork. I’d be surprised insurance companies don’t use something similar already.
Don’t forget the inherent biases that are introduced with AI training! Women especially have a history of having their symptoms dismissed out of hand - if the LLM training data includes these biases, in combination with the bad diagnosis women could be really screwed.
similarly to people from different races/countries … it’s not only that their conditions might vary and require more data, it is also that some communities don’t visit/trust hospitals to even have their data collected to be in the training set. Or they can’t afford to visit.
Sometimes, people from more vulnerable communities (eg LGBT) might prefer not to have such data collected in the first place, making data sparser.
. The rate dropped further when it came to differential diagnosis, implying chat gpt was leaving out important rarer possibilities.
Every decade, new diagnoses and discoveries are made. Many manmade or climate change related. We never had microplastic poison before. Or random chemicals added into our foods because it gives a company that +1% profit.
In other words, we are finding new ways to destroy our bodies!
And with AI is always working with historical data, it’ll be a long time before we only use a AI Doctor.
Anecdotally my doctor is prolly only right 75% of the time too. But I’ll go back to him later with more information about the ailment (or more tests) and he’ll eventually get it right. Medical diagnoses in general are not terribly accurate.
AI could ultimately improve both the efficiency and the accuracy of diagnosis as healthcare in the U.S. gets more expensive and complicated as individuals live longer, and the overall population ages
When you read some bs on internet but thankfully its US only
