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I mean, have you used GPT-4? Free form text is its bread and butter, and yes, it can absolutely ingest images and read text in them, and combine that with other

I mean, have you used GPT-4? Free form text is its bread and butter, and yes, it can absolutely ingest images and read text in them, and combine that with other information from multiple sources in structured or unstructured text or image form, no problem! What you are describing sounded decades away last year. Today it's not something you can rely on quite yet if you need accuracy. But if you still believe it's decades away then you need to update your perception of what's going on in AI right now. Forget the free GPT-3.5 or Bard, you really need to try GPT-4 to understand what's about to happen.

dogmatism 3y ago
see my comment above Pt sees Dr in office A, has labs and scans ordered. Labs order is printed out and given to pt, who takes it to lab A. Scan #1 is ordered, and order faxed to facility B, who independently calls, schedules, performs, and interprets scan #1, same for scan #2, but at a different facility. Office A has no electronic link to any of these facilities How does LLM get the data? A human knows the patterns in the area, and calls around for it, then collates it and feeds in to office A's EHR, where if lucky, LLM can do it's thing LLM is only saving the bare minimum of the work In an industry that is still reliant on the fax, I'm not holding my breath for the advent of the LLM savior
- modeless 3y ago
  In the situation you describe humans fail constantly. My experience with the medical system has decidedly not been that magically competent back office people call every office you've ever visited to assemble your complete medical history from scraps and effectively organize it for the doctor. It's a constant game of telephone where you have to do most of the work yourself, calling around and giving instructions to receptionists to give to other people to get this stuff done. They can't even communicate reliably between the nurses and doctors in the same damn office to avoid asking the same questions multiple times every time you visit. What you describe, if it worked reliably, would be an advance over current human-level average performance. And AI will absolutely be able to do it, too. Probably within ten years, though it will take longer to deploy after the capabilities are there.
  - dogmatism 3y ago
    No, you’re right, it doesn’t work reliably I just think the y combinator crowd underestimates the human obstacles and ancient tech in the path of getting AI implemented
    - staunton 3y ago
      That only concerns the time needed to implement it though, not capabilities. If an AI is known to be significantly better at diagnosing than your GP, and you know and believe this (this of course has yet to happen and then take time to be noticed by people), then you will use it. You will demand it is used. People actually care about their health.
- comradesmith 3y ago
  Not hard to strap GPT voice to a phone line, and provide it with some information of local labs and their contact information. Also you said the office doesn’t have an electronic link but your example workflow includes the phone ;)
- vidarh 3y ago
  What you're describing is a process and information management failure that ought to be addressed first, sure. I book a video consult. I talk to a doctor, who has an initial description of my symptoms from my booking on her computer. She takes notes on a computer (I have access to them). If needed, she orders labs on a computer. I go in, and there is no paper, just an electronic record, and while there may well be paper in the process in some instances behind the scenes, data entry people ensures it is all added to the electronic record. If labs are not needed, she'll submit my prescription electronically to my local pharmacy. This is how it's worked when I talk to my doctor for years (UK; not nearly all GPs have gone this far) It may well "only save the bare minimum" of the actual labour happening behind the scenes, but with a well functioning system, it saves the expensive, resource constrained part of the work.
- IanCal 3y ago
  > How does LLM get the data? * Run database query to see where the type of scan is typically ordered (we know they can generate sql pretty alright) * * Alternatively someone at one point needs to just make a list * Call the office (voice conversations is clearly possible, it's a feature in chatgpt as an app) * Receive fax * gpt-4-vision or OCR then GPT-4 or however you want to interpret the data It's not like it's not work to build something like this, but all the pieces are right there.
whatshisface 3y ago
This reminds me of what happened in self-driving. It went from "decades away," to "it works but you can't quite rely on it for accuracy" in a year and then it stopped cold for some reason.
- kridsdale1 3y ago
  Because it kept crushing peoples knees.
- staunton 3y ago
  Useful Full-Self-driving is arguably harder than "useful automated medicine" in two ways. First, you need insane reliability to match human performance. Much higher reliability than doctors even. Second, it's not "just" information processing somewhere in the cloud. It has to run in real time inside a car. Both are very hard in that the conditions are very context dependent and vary a lot (a.k.a. the real world is messy).
- krisoft 3y ago
  > and then it stopped cold for some reason By stopped cold you mean "there are actual real world self driving cars delivering actual real world passengers in select locations"?

dogmatism 3y ago

see my comment above Pt sees Dr in office A, has labs and scans ordered. Labs order is printed out and given to pt, who takes it to lab A. Scan #1 is ordered, and order faxed to facility B, who independently calls, schedules, performs, and interprets scan #1, same for scan #2, but at a different facility. Office A has no electronic link to any of these facilities How does LLM get the data? A human knows the patterns in the area, and calls around for it, then collates it and feeds in to office A's EHR, where if lucky, LLM can do it's thing LLM is only saving the bare minimum of the work In an industry that is still reliant on the fax, I'm not holding my breath for the advent of the LLM savior

modeless 3y ago
In the situation you describe humans fail constantly. My experience with the medical system has decidedly not been that magically competent back office people call every office you've ever visited to assemble your complete medical history from scraps and effectively organize it for the doctor. It's a constant game of telephone where you have to do most of the work yourself, calling around and giving instructions to receptionists to give to other people to get this stuff done. They can't even communicate reliably between the nurses and doctors in the same damn office to avoid asking the same questions multiple times every time you visit. What you describe, if it worked reliably, would be an advance over current human-level average performance. And AI will absolutely be able to do it, too. Probably within ten years, though it will take longer to deploy after the capabilities are there.
- dogmatism 3y ago
  No, you’re right, it doesn’t work reliably I just think the y combinator crowd underestimates the human obstacles and ancient tech in the path of getting AI implemented
  - staunton 3y ago
    That only concerns the time needed to implement it though, not capabilities. If an AI is known to be significantly better at diagnosing than your GP, and you know and believe this (this of course has yet to happen and then take time to be noticed by people), then you will use it. You will demand it is used. People actually care about their health.
comradesmith 3y ago
Not hard to strap GPT voice to a phone line, and provide it with some information of local labs and their contact information. Also you said the office doesn’t have an electronic link but your example workflow includes the phone ;)
vidarh 3y ago
What you're describing is a process and information management failure that ought to be addressed first, sure. I book a video consult. I talk to a doctor, who has an initial description of my symptoms from my booking on her computer. She takes notes on a computer (I have access to them). If needed, she orders labs on a computer. I go in, and there is no paper, just an electronic record, and while there may well be paper in the process in some instances behind the scenes, data entry people ensures it is all added to the electronic record. If labs are not needed, she'll submit my prescription electronically to my local pharmacy. This is how it's worked when I talk to my doctor for years (UK; not nearly all GPs have gone this far) It may well "only save the bare minimum" of the actual labour happening behind the scenes, but with a well functioning system, it saves the expensive, resource constrained part of the work.
IanCal 3y ago
> How does LLM get the data? * Run database query to see where the type of scan is typically ordered (we know they can generate sql pretty alright) * * Alternatively someone at one point needs to just make a list * Call the office (voice conversations is clearly possible, it's a feature in chatgpt as an app) * Receive fax * gpt-4-vision or OCR then GPT-4 or however you want to interpret the data It's not like it's not work to build something like this, but all the pieces are right there.

whatshisface 3y ago

This reminds me of what happened in self-driving. It went from "decades away," to "it works but you can't quite rely on it for accuracy" in a year and then it stopped cold for some reason.

kridsdale1 3y ago
Because it kept crushing peoples knees.
staunton 3y ago
Useful Full-Self-driving is arguably harder than "useful automated medicine" in two ways. First, you need insane reliability to match human performance. Much higher reliability than doctors even. Second, it's not "just" information processing somewhere in the cloud. It has to run in real time inside a car. Both are very hard in that the conditions are very context dependent and vary a lot (a.k.a. the real world is messy).
krisoft 3y ago
> and then it stopped cold for some reason By stopped cold you mean "there are actual real world self driving cars delivering actual real world passengers in select locations"?