GPT-4 performance comparable with physicians on official medical board residency examinations. Model performance near or above official passing rate in all medical specialties tested
GPT-4 performance comparable with physicians on official medical board residency examinations. Model performance near or above official passing rate in all medical specialties tested
It's just a multiple choice test with question prompts. This is the exact sort of thing an LLM should be very good at. This isn't chat gpt trying to do the job of an actual doctor, it would be quite abysmal at that. And even this multiple choice test had to be stacked in favor of chat gpt.
Because GPT models cannot interpret images, questions including imaging analysis, such as those related to ultrasound, electrocardiography, x-ray, magnetic resonance, computed tomography, and positron emission tomography/computed tomography imaging, were excluded.
Don't get me wrong though, I think there's some interesting ways AI can provide some useful assistive tools in medicine, especially tasks involving integrating large amounts of data. I think the authors use some misleading language though, saying things like AI "are performing at the standard we require from physicians," which would only be true if the job of a physician was filling out multiple choice tests.
I, too, can pass the Boards if you remove all the questions I don't understand.
I’d be fine with LLMs being a supplementary aid for medical professionals, but not with them doing the whole thing.
I wonder why nobody seems capable of making a LLM that knows how to do research and cite real sources.
I mean LLMs pretty much just try to guess what to say in a way that matches their training data, and research is usually trying to test or measure stuff in reality and see the data and try to find conclusions based on that so it doesn't seem feasible for LLMs to do research
They maybe used as part of research but it can't do the whole research as a crucial part of most research would be the actual data and you'd need a LOT more than just LLMs to get that
Yup! LLMs don't put facts together. They just look for patterns, without any concept of what they are looking at.
Have you ever tried Bing Chat? It does that. LLMs that do websearches and make use of the results are pretty common now.
Bing uses ChatGPT.
Despite using search results, it also hallucinates, like when it told me last week that IKEA had built a model of aircraft during World War 2 (uncited).
I was trying to remember the name of a well known consumer goods company that had made an aircraft and also had an aerospace division. The answer is Ball, the jar and soda can company.
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Because the inherent design of modern AIs is not deterministic.
Adding a progressively bigger model cannot fix that. We need an entirely new approach to AI to do that.
Bigger models do start to show more emergent intelligent properties and there are components being added to the LLM to make them more logical and robust. At least this is what OpenAI and others are saying about even bigger datasets.
For me the biggest indicator that we've barking up the wrong tree is energy consumption.
Consider the energy required to feed a human with that required to train and run the current "leading edge" systems.
From a software development perspective, I think machine learning is a very useful way to model unknown variables, but that's not the same as "intelligence".
Cohere's command-r models are trained for exactly this type of task. The real struggle is finding a way to feed relevant sources into the model. There are plenty of projects that have attempted it but few can do more than pulling the first few search results.
What would be much more useful is to provide a model with actual patient files and see what kills more people, doctors or models.
I would watch that show.
GPT will require every test and yet for the sake of authenticity randomly perform medical errors.
All these always do the same thing.
Researchers reduced [the task] to producing a plausible corpus of text, and then published the not-so-shocking results that the thing that is good at generating plausible text did a good job generating plausible text.
From the OP , buried deep in the methodology :
Because GPT models cannot interpret images, questions including imaging analysis, such as those related to ultrasound, electrocardiography, x-ray, magnetic resonance, computed tomography, and positron emission tomography/computed tomography imaging, were excluded.
Yet here's their conclusion :
The advancement from GPT-3.5 to GPT-4 marks a critical milestone in which LLMs achieved physician-level performance. These findings underscore the potential maturity of LLM technology, urging the medical community to explore its widespread applications.
It's literally always the same. They reduce a task such that chatgpt can do it then report that it can do to in the headline, with the caveats buried way later in the text.
This research has been done a lot of a times but I don't see the point of it. Exams are something I would expect LLMs, especially the higher end ones, to do well because of their nature. But it says next to nothing about how reliable the LLM as an actual doctor.
Even those who do well in testing of wrote knowledge can perform poorly in practical exercises. That’s why medical doctors have to train and qualify through several years of supervised residency before being allowed to practice even basic medicine.
GPT-4 can’t do even that.
But it says next to nothing about how reliable the LLM as an actual doctor.
Yet these tests say anything about how a human would be as an actual doctor?
The 17th percentile in peds is not surprising. The model mixing it's training data with adults would absolutely kill someone.
Google started killing the Dr industry (gp) Ai will finally be the nail in the coffin except Drs will never give up the power to prescribe
LLMs can't design experiments or think of consequences or quality of life.
They also don't "learn" from asking questions or from a 1-time input. They need to see hundreds or thousands of people die from something to recognize the pattern of something new.
Yeah but they can give the common answers of bed rest and hydration that is a drs go too for every thing.
I imagine a future where LLM take over the menial up duties of you have a cold, you have high blood pressure etc.
So actual Drs spend more time doing less menial tasks.
But since as a society we develop automation and fire everyone around it i cant see it really happening