Inventor: "We programmed the best surgeon’s techniques, based on consensus and physics, into the machine"
Third Party: “While in a technical sense, semi-autonomous suturing is a ‘grand challenge’ problem of surgical robotics, clinically much suturing and bowel anastomosis is done by staplers which can do the whole thing in seconds,” he wrote in an email. “Clearly the task they chose does not justify the elaborate equipment they used.”
So, they used machine learning to perform a limited part of a surgical procedure, but with freedom of motion and adapting to tissue changes.
At the end of the article they talk about self-driving cars and how we have lane-assist and the next level is taking over. The inventor likens this technology to current lane-assist technology, but it seems more involved than that.
Personally I do not want any machine learning consensus algorithm with control over a surgical procedure in my body. I think the DaVinci type systems (tele-operation, but without autonomy) are awesome -- they allow superhuman precision in delicate surgical tasks.
However, until AGI is a solved problem I do not want an automated algorithm making decisions with a knife to my organs.
Let the automation algorithm highlight portions of the screen or anticipate the next viewpoint, but keep it away from the controls.
I'm with you. The sheer amount of human error in the medical field that causes death and injury is astounding [1], and I would gladly put my life in the hands of a capable machine instead of a fallible human if given the choice.
I would already be happy if medication for a patients wouldn't be handled by passing paper notes from one nurse to the next. There is no fancy machine learning needed to make sure that you get what the doctor prescribed in the correct dose.
Where do they still do that? I live in a developing country (some people call it third world) and the private hospitals here have been using all electronic medication ordering and fulfilment for quite a while, at least since 2009[1].
Doctor enters the prescription into a networked computer. It goes to a robotic pill picker/packer that affixes the label with instrucitons. Outpatients pick up the medication at the desk on the way out. For inpatients it is sent to the nurses' station on the floor of their hospital room.
It's been a while since I've been to a hospital in the US. I just assumed they were already doing this.
It is a big change from the traditional shift change in many hospital units, where nurses going off duty typically confer in a hallway or at the nursing station with the nurse coming on for the next shift, giving a rundown of their patients’ status and needs. In some cases nurses may simply write up a report in the medical record for the next shift to read.
It also 'helps' that EHR software has been forced onto hospitals at such an early point. My father constantly checks what orders are given to a patient now because one time, an order he placed at a patient's previous visit to the hospital was placed at the current patient's visit instead, almost two months later. Luckily the screw up was just with food assigned to the patient (high fiber diet vs liquids), but imagine if it was something like a drug being prescribed.
I work with EHRs. Patient context bugs (patient number, visit number, chart number, encounter number, or any combination thereof) don't come up THAT often but it seems like everyone has them. It's actually surprising the occurrence is low since most of them are giant piles of WinForms spaghetti by now.
But then again the software in those machines will be written by humans and will most likely have bugs - which might influence the outcome of the operation. So the questions is whether you trust more the surgeon or the engineers of that machine.
As an earlier poster said, it is nothing to do with "trust". Software has bugs, surgeons make mistakes. What matters is the relative degree of statistical risk.
If the risk of falling victim to a bug/mistake by a software surgeon is lower than that of a human surgeon, then simple desire for self-preservation you should choose the software. To choose the human over the software, even when it's provably more dangerous is allowing a baseless prejudice to put you at higher risk. It's equivalent to being given the choice between two human surgeons of differing skill levels, and choosing the lesser skilled surgeon on the basis of their ethnicity.
How about a surgeon that's been up for 36 hours, hungry, with a splitting headachy, and some family problems on the mind. A human surgeon might be awesome and can still make a ton of mistakes for reasons unrelated to their medical abilities. Meanwhile, while a programmer could easily make a mistake, other people and tests of the code could spot a lot of mistakes that could be corrected before the system reaches its first patient.
I'm going to take a different tack: How about we stop hazing medical professionals at the beginning of their career and only ask them to work 8 hour shifts with an appropriate amount of time off until their next shift?
Along with lmm's comment, where would all the extra doctors come from? You can't cut hours worked in half (or close to it) without doubling your staff to meet the demand. US hospitals (especially ERs) are already running over patient capacity in many US cities
Simple, make the hell of residency go away, and allow more foreign doctors to come in to US and practice after going through a reasonable residency program. I have known very smart and competent Russian and Ukrainian doctors who work as lab employees because they are not allowed to practice medicine here.
Great idea. But how do we get to there from here? Particularly when doctors' professional bodies are large, powerful, and full of people who are convinced that that never did them any harm?
As a software developer who has been stitched back together by an MD who has been on shift for 36 hours, I'm with the machine also. No relevant paternal affiliation.
My guess is that the software will be better at the well know tasks. And similarly to automatic cars, they will struggle with the unusual scenarios. (Saying that I don't know a great deal about surgery).
I'd argue that a surgeon's time is wasted doing grunt engineering work, they are better as project managers and test engineers because they can come up with tests to prove it works better than the engineers. It's rare for someone to excel at two scientific fields, and you'd need excellent engineers for that kind of project.
I don't think you'll see fully automated surgery soon because most ML algorithms can too easily be fooled by unusual sensor data or unexpected states -- and these are very much AGI problems as well. Those algorithms are no where near the reliability levels required for approval as medical devices. We will have advanced assist-mechanisms (like davinci robots) long before the decision making processes are incorporated into a robot surgeon. Essentially, there won't be a "computer surgeon" for a long time and the difference between Human Surgeons using modern assist technology vs a fully computer surgeon mortality will be blurred as assistance technology improves. So there will never be a 1% vs 0.5% mortality. It will be equal mortality at best before AGI allows improvements under as many or more conditions as a human. Just my opinion of course.
I would guess the automatic parts will be like a toolkit of tasks which the surgeon can delegate to an algorithm. You could imagine that an algorithm could sew skin together with a level of accuracy to prevent scarring, rejoin nerve and small blood vessels quicker and more accurately, or remove cancerous tissue tagged with a biomarker, while avoiding nerves or important structures nearby.
The surgeon could put the surgery into the controlled situation that the algorithm understands, and make some over-arching decisions through a UI (for instance, he could say 'join this nerve on this side to this nerve on the other', which might be difficult for the algorithm to work out), and then the algorithm would accomplish that task, and return control back to the surgeon.
More simply, a program could prevent a human surgeon using a machine like a Da Vinci from touching a nerve, or define the limits of bone removal.
The latter example does already exist in clinical use:
That may never come. The best-performing machine learning algorithms work by optimising a measure of error. Experience says that while it's easy enough to take this error to something between 10% - 30%, it's excruciatingly difficult to push it any further down.
see, I'm with you WHEN that's the comparison for the particular surgeon who would be performing my procedure. Not the average of all surgeons vs the computer, since that stat is not necessarily applicable to my situation.
You might hope the be the special snowflake who gets the heroic surgeon, but I wouldn't bet on it. Unless you are medically interesting in some way, you're likely to just get the next schmoe on the rotation.
> However, until AGI is a solved problem I do not want an automated algorithm making decisions with a knife to my organs.
AGI isn't yet discovered yet we allow planes to fly themselves, markets allow automated agents to spend billions and so on. What if the algorithm was proved to be 10x safer than a human expert? Even without AGI they could be better than humans.
> Personally I do not want any machine learning consensus algorithm with control over a surgical procedure in my body
Isn't the surgeon's brain a machine learning algorithm in physical form? Humans are more versatile today and can adapt do different situations, but I don't see this as a argument against machine learning necessarily.
Inventor: "We programmed the best surgeon’s techniques, based on consensus and physics, into the machine"
Third Party: “While in a technical sense, semi-autonomous suturing is a ‘grand challenge’ problem of surgical robotics, clinically much suturing and bowel anastomosis is done by staplers which can do the whole thing in seconds,” he wrote in an email. “Clearly the task they chose does not justify the elaborate equipment they used.”
So, they used machine learning to perform a limited part of a surgical procedure, but with freedom of motion and adapting to tissue changes.
At the end of the article they talk about self-driving cars and how we have lane-assist and the next level is taking over. The inventor likens this technology to current lane-assist technology, but it seems more involved than that.
Personally I do not want any machine learning consensus algorithm with control over a surgical procedure in my body. I think the DaVinci type systems (tele-operation, but without autonomy) are awesome -- they allow superhuman precision in delicate surgical tasks.
However, until AGI is a solved problem I do not want an automated algorithm making decisions with a knife to my organs.
Let the automation algorithm highlight portions of the screen or anticipate the next viewpoint, but keep it away from the controls.