PMC-LLaMA: Further Finetuning LLaMA on Medical Papers
arxiv.org
arxiv.org
However, in the paper they say that for each of the 5 epochs, they sample 512 tokens from each paper randomly.
This would come down to an effective training size of 12 billion tokens.
Zero shot comparisons are not shown.
This looks like a failed experiment to me?
And yes, training on top of LLaMA could introduce a lot of unexpected behavior, but that's just where the State-of-the-Art is today
Could definitely use some more exposition around that though.
Wouldn't you?
If you asked me in 1995 would I bet my money on World Chess Champion or a computer? ask that again 4 years later.
At some point I will trust cars to drive us more than us to drive cars.
These "gotcha" statements aren't helpful.
When you get diagnosed by a doctor, usually no one checks the diagnosis. I would love if my health was checked by medical professional committee. Human and/or AI.
You'd have to join the social network groups for doctors to see that, but there's a lot of double checking happening both with local peers and wider groups. For the more interesting cases anyway... you're not getting a second review if you come in with runny nose and test positive for RSV. (Edit: and even in more complex cases you may not get it for a lot of reasons)
(But, yeah, we have plenty of software developers confidently checking in untested, unreviewed code too)
> The researchers estimate that 7.4 million misdiagnosis errors are made every year, 2.6 million people receive a harm that could have been prevented, and another 370,000 are permanently disabled or die because of the misdiagnosis.
Source: https://edition.cnn.com/2022/12/15/health/hospital-misdiagno...
2. and 3. are interlinked. In my mind, medicine is the number one application for ML. Every doctor should have the best AI at their finger tips. One person cannot digest all the research that is being done; computer can. The benchmarks will go up.
First person thinks it's X, second person doesn't, first person changes mind but it really was X.
First person thinks it's X, second person finds potential issue Y which becomes more important, but X was actually the biggest issue.
The thing about mistakes is that you often don't expect you're making one. To my mind there is still value in having a built-in second opinion.
The amount of times I've heard doctors tell female friends that their issue is "hormonal" is frankly offensive. Perhaps if we can create an AI (assuming it also doesn't say women have the modern equivalent of "hysterics" for every problem) they will finally get a real answer.
And the answer is the same: Thorough testing and vetting and auditing out any adverse outcomes is what makes or would make either safe enough. Once an LLM is thoroughly tested and shown to perform at least as well as a real doctor, without any worse worst-case outcomes, then sure.
So, not yet.
which means over 75% of the population would chose this immediately
and of the people that are content with their medical attention, a good portion of them would also choose this
tl;dr yes
I’m a straight white man and I’ve had plenty of dismissive doctors over the years too. It turns out arrogance, laziness, or a lack of time have little to do with the patient themselves.
This doesn't make you a bad person btw, just means you are not aware of how small your social context is.
When I was 17 I went in to the doctor because of extreme fatigue. He just slapped me on some antidepressants and called it a day. Years later I happened to read about low testosterone symptoms, which matched me very well. He eventually acquiesced to letting me test, and it came back 2 points above the low end of normal - which probably by itself qualified as low for my age. He wouldn't let me do a quick trial of testosterone supplementation nor test again, but I begged him to refer me to an endocrinologist.
The endocrinologist (2 hours away) was worse. 100% dismissive, straight up told me I didn't have low testosterone. He did however let me test again, and this time I was 150 below normal. I asked to be put on medications that would maintain my fertility. He told me I didn't need to worry about losing my fertility on straight up testosterone, which is 100% false.
I'm going to cut the story off there, but it keeps going. My dad almost died because doctors didn't diagnose his lupus. My sister's friend lost her father when we were young because of an infection after some dental work where they dentist completely dismissed his pain after the fact.
Everyone is unaware of how "small their social context is," which is exactly my point. If I were a minority I very well might be blaming my story on that.
Somebody you love is in an life threatening condition. You need advice what to do or you lose them.
You have a one shot option to get advice from a human expert or a LLM.
Which one you pick.
Countless ink has been spent on discussing the potential risks and dilemmas of automated decision support, e.g., the autopilot situation having to choose whom to save.
It is not "stupid" to isolate the essence of the challenges we are facing and discuss them without hidden agendas.
Incidentally such discussions also help cast much needed light on tech bro culture and morality.
I’ll pick the LLM. The humans are too random. I’ll take my chances with “hallucination” from something that’s also read every research paper in every language. Its just like Flowers for Algernon but even better.
There's no good reason yet to expect that the 75% would receive better diagnosis from from the AI.
Our group, sure! Our generation, and people in our shoes, and with our level of knowledge about LLMs. But maybe not others.
tl;dr Not yet
Consider three things:
1. What people prefer when it comes to intimate/private issues that a physician diagnoses.
2. Tainted source datasets, resulting in the same "dismissive diagnosis" from the LLM
3. Lack of Trust held within a new system
1. For starters, there are certainly a large subset of people that simply "don't trust machines". Alternatively, they "don't trust major corporations". They would likely pick local doctors over machines, due to a perceived lack of connection/humanity in the LLM. Combine that with the recent increased use of LLM / AI models used to make scam calls, and you have a potentially deep seated (and at times illogical) distrust of any LLM diagnosis.
Some would say the machine doesn't and cannot understand their unique situation. And refuses to give them what they need. So they would go to a doctor. Some would have difficulty being honest with a machine. Would you trust a human or a machine to keep your medical records safe? (I honestly don't know which I would trust. Both at the same time preferably?)
2. Others would say the dataset is made up of biased diagnoses specifically tailored towards the majority, and fail to diagnose the minority correctly. You are assuming that the LLM cannot be tainted by biased or dismissive diagnosis made by doctors against the very same women and minorities. The datasets have to come from somewhere, and some of that data will without a doubt be biased.
3. There is a lack of trust. Automated systems are making great strides yes. But absolutely no one trusts them fully. Whether it be planes, cars, logistics, data, etc Absolutely no one trusts them fully. Especially with GPT like systems that simply cannot say "No" and start making stuff up.
Remember the fiasco with Bard gaslighting someone about the current year? Imagine if that happens during an LLM diagnosis.
Come full circle, those same people who don't trust a human physician due to discrimination? "Why the hell would I trust an AI machine made specifically to make money!". What is there that actually makes a corporate AI more trust worthy than the local physician? What is there that actually prevents the LLM from discriminating?
This is really my main concern: Nothing stops the LLM from discriminating. All it takes, is a dataset with built in biases.
It isn't nearly as clear cut as you make it out to be.
A medical paper isn't just a digestible blog post or conversational op-ed, it's full of technical jargon and statistics that even require expert readers to do some unpacking in order to evaluate how the presented findings fit into a larger picture. Indeed, it's a skill and often a form of art to be able to read and understand medical papers, even from within one's field of expertise. Aside from that, medical knowledge is never truly established, it is always in flux, both in respect to ongoing research and in the skill that derives from decade long practice of negotiating this with often more complex and nuanced real-world situations, i.e. with the patients that come through the doctor's office doors.
Doctors already face(d) the toll of diagnosis within a Google search's reach: misinformed, anxious and often outright overconfident patients often stand in their own way. That is not to say, that medical literacy and knowledge for the masses would be a detrimental thing, quite the contrary is true. However, with the high stakes faced in medicine, any misinformation, be it by Google or LLM can lead to grave harms.
While doctors face google, patients face poor doctors. My father is 96, so lots of things have inevitably started to go wrong. Knees, heart, bladder, prostate, blood pressure. His doctor is absolutely shit. He started feeling light-headed a few months back and the doctor confidently pronounced that he's just old. My mother intervened. Turns out the handfuls of pills he's been prescribing my father included blood pressure pills, and if he ha bothered taking routine blood pressure readings the doctor would have realized that my father's blood pressure was dangerously low. He quit those pills and bounced back. His doctor has been useless, lazy and shamelessly apathetic for 10 years. Terrible doctors are everywhere. My wife's doctor told her that her extremely heavy periods just happen to some women. Oh, and that her chronic anemia and B12 deficiency were normal in some women, so he'd just keep giving her those shots. She demanded a scan, which revealed a fibroid but the doctor told her: "oh, you can just go on the pill!" It took another doctor to schedule a procedure to remove the fibroid. She's been fine for a decade since. But has met many women online who went through hell with untreated fibroids. One woman said that it ruined her life because her anemia was disabling, her heavy periods left her housebound, and when the fibroid finally reached the size of a grapefruit she had to have a hysterectomy. Up to that point her doctor called her a hypochondriac.
Oh, and when my sister told her doctor that she had "new" pains 2 months after giving birth, he told her it was normal, take pain killers and go home. It took several attempts before she convinced him to schedule a scan. Turns out it was terminal cancer! I don't even know that catching it a few weeks earlier would have changed anything, but still. Err on the side of caution.
The thing about a decent LLM doctor, if one were to exist, is that it won't get bored, apathetic, depressed, tired, hateful etc.
It will, however, have had the standard biases RLHF'd into it.
It's just a matter of time before we see a HN Launch for a startup that's going to disrupt the medical industry with LLM.