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ChatGPT definitely would not help there. And not even ML in general. What you want to accomplish is more related to the field of robotics and control systems.

The overlap between ML and robotics is increasing day by day...

What do you have to dedicate to this?

Time? Money? How much of each?

If it's just your time, I would start with hobby/kit robotics stuff, perhaps remote controlled (ie. Nothing smart) and show it doing dental work on plastic models of teeth with real tools. Then make a YouTube channel about your work, successes and failures.

That YouTube channel will hopefully get the next generation interested in actually doing the task properly.

If you have serious money to dedicate to the cause, I would try to start a startup, hiring a robotics expert, and someone who has previously worked in the medical devices field (there are soooooo many laws - navigating the legal landscape is probably trickier than making a robot do a filling). Obviously you should also go get VC funding wherever possible, but by putting in a chunk of your own money that will be far easier.

I think in your position the most valuable thing you could do is to collect and provide dental training data to experts. You could also try to get in contact with a local university and see if they have some (future) medical/dental AI projects for their students and scientists which you could support by providing expert knowledge

this is by far the most useful thing to do, OP. Sure, you can start learning the ML basics, but it's going to take a very long time until you can contribute something useful to the field if you start from 0. Data, however, is the big filter for ML projects and you are in the unique position to be able to collect such valuable data.

Get in touch with a local university and see how you can help them out

idk why the idea of a robot digging into my teeth while i'm strapped to a chair seems terrifying.

Take a look at computer vision techniques in general.

Half of the challenge in doing what you want to achieve is to measure the mouth of the patient, and locate the medical instruments w.r.t. it.

Find a partner with expertise in robotics and computer vision, that will help with the technical part.

This is a conversation that would be best be had with researchers who are already well immersed in the fields relating to remote and automated medical procedures. It's a vibrant area of research that has a fairly low degree of public awareness because of how many different disciplines are required to interact at an incredibly high level of fidelity and reliability under the extremely unpredictable environment of the human body.

Groups like the Scientific Computing and Imaging Lab at the University of Utah (with whom I have no affiliation but I have followed their work for decades) have been working in partnership with similar labs around the world for years to pioneer the types of technology you'd like to support and explore. By far, your best bet is to start understanding who the active research centers are, begin to learn the types of problem-solving resources that exist and the types of challenges that are specific to your medical domain, and find the areas within the vast array of resources that will inspire and motivate you through the rest of your journey.

I say all this not to discourage you, rather to encourage you to prepare appropriately for the mountain you're looking to climb. The foundations for this type of work have grown steadily for five decades, so you have a strong, resilient terrain upon which to build a legacy.

I would encourage you to consider a biological approach. Many dental problems are caused by oral bacteria. If it’s possible to change the micro biome inside the mouth, it would be the biggest revolution in the history of dentistry.

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agreed. MLs impact for dental health would be a orders of magnitude larger if channeled into biological discoveries or prevention based on saliva analysis or eating habits stats than with precision robots. Granted the latter would make much cooler headlines.

Most valuable would probably be if you advise people what not to do. Or why it might be a bad idea. That would be much more valuable, as ML Engineers have no idea about that.

I admire your passion and good intentions, but why do people think they can fundamentally contribute (laying the groundwork) to the SOTA of a technical field without any background and limited time. Thousands of PhDs working on AI dedicate almost every minute of their lives to this field, and only a small minority is able to make significant contributions that lay the groundwork for anything at all.

Nobody expects to be able to become a surgeon as a hobby; why do people expect to do excellent ML research as a hobby? Additionally, with all due respect, your paragraph further shows very limited understanding of current surgical robotic technology and ChatGPT.

The best way you can contribute is to work with ML experts and offer domain knowledge or data — do not expect to contribute on a technical/foundational level as a hobbyist.

Do you actually work in ML research lol? About as important as fundamental research on architectures losses and optimisers is the applied end of things and tons of applied stuff is absolutely something other domain experts can contribute to, non ML non CS expertise is absolutely essential to i.e. the stuff my group does. "State of the art on some famous benchmark" is not the be all and end all of this field and "only a small minority is able to make significant contributions" is an absurdly incorrect statement.

Seems terrifying bcs if you strart vibrating from pain a dentist will stop immediately while a robot will probably just hold your head with 1 hand and continue drilling. I really hope AI robots (autonomous or not) nvr come to fruition.

Robots make mistakes, but they’re heavily regulated. Being in the industry I know humans make many, many more mistakes .. worse still many of them don’t learn from their mistakes but keep making them it until they retire.

Only a small minority is able to make significant technical contributions. I may have misinterpreted his angle of groundwork, but as he mentioned resources to try and learn ML I assumed he meant technical. As I said domain knowledge and/or providing data and relying on the technical expertise of others is the most valuable direction to go. I think we are actually in agreement here.

I myself work with engineering groups on some applied projects and a lot of the 'applied ML' outside of CS is absolutely horrendous.

I took the plunge many years ago. Quit clinical work and dedicated myself to developing and emerging technologies. Was a difficult decision but I knew that’s where everything was headed.

Hate to say this, but being in the industry I can tell you that the public should be more terrified of people than the robots. Sure robots can make mistakes, but humans make many, many more.

There are already some products in use, Yomi is an FDA approved robotic solution for dental implant surgery. I have also seen a robot for automatic crown preps but it’s still in development.

Intraoral scanner companies have invested heavily in AI; first for better scan results, now for diagnostics and treatment planning.

And that’s just the start of it, it’s honestly been a privilege to be able to peek behind the curtain and see what’s coming next, it’s really amazing.

Like others said, working with Universities and research institutes is a great way to contribute your knowledge and potentially build something game changing. Good luck!

Important though to note are literally not enough people just taking stuff implemented in scikitlearn or whatever and applying that to their own problems, and in and of itself that can be novel and interesting even if its not a shiny new model.

> As I said domain knowledge and/or providing data and relying on the technical expertise of others is the most valuable direction to go.

Its mainly the way you wrote your comment that left a bad taste in my mouth, this line specifically is probs a fine recommendation for OP.

I expect a human to stop when I flinch and I'm in pain. I don't expect a robot to do that. At least not until I see thousands of operations done automatically with no victims.

I’ve seen many a doc not stop when they should have.

Source: Read 10 years of disciplinary reports and was positively horrified…. Way worse than I ever would have believed

Medical robotics is a field that is booming now and that is hungry for tech-inclined licensed practitioners to join them. Just go advertise yourself to startups in the field, I am sure you will get interesting proposals.

I have just retired from another medical domain.

TBH 95%+ of my job could have been automated.

A nurse or similar with basic training could have operated the equipment, and an AI could have instructed her/him of the required actions.

My main contribution was quizzing the patient to elicit what really was going on, and not what they said was happening.

A personal AI avatar could do this work - or the nurse could be prompted to ask a series of targetted questions.

No doubt, many medical domains could be fully (or almost so) automated,

You know laser eye surgery has been around for a long time right? Blasting potentially blinding lasers into your eyes is risky too, these products only see the market after years of proving themselves in controlled settings.

Once a doctor passes their exams, that’s the last time anyone really pays attention to what they’re doing. That should make you more nervous.

You can try to help by creating a speedy way to pass info, like an image from a X-ray to cartesian robots with and plastic extruder (aka 3D printers).

In this way you can make custom braces and prothesis very cheaply and a help a lot of people.

I agree that the tone of my original comment was overly snarky.

The challenge to learn ML for a middle-aged dentist is immense, and probably not where his best uses lie. I was fearful most on here would just tell him to take the plunge. But I see that others have gotten my point across much more eloquently (and not as snarky ;) ).

ML is used as a tool in robotics, but there is much more to a successful robotics project than ML.

>I would like to take part in laying groundwork for future autonomic robots powered by AI that are capable of performing dental procedures.

Why?

Everybody lies.

The AI tools we have now seem too trusting and take users input at literal value. I wonder what research would suggest about making AIs more skeptical towards humans that need their help.

Also, trusting an AI that doesn't trust its users sounds sketchy.

> New robot dentist, now with only a 1 in 1000000 chance to mistakenly drill into your bones!

i think you've got the right idea about getting involved. i would say that your expertise would be wasted if you try to do the ML stuff yourself. you should definitely leverage your biggest asset as a domain expert and find some ml researchers who can be the tech experts. others have pointed out how reaching out to universities can be a good way to start. maybe you can look into some medtech startups that would like to have a chat with your about this stuff

in terms of getting to know the tech itself, you should have some layman's understanding of how the ml works. for that i'd recommend finding some good ml content geared towards enthusiasts rather than professionals. stuff like computerphile's videos on models and concepts like GPT, diffusion models, encoder decoder networks, and deep learning in general. you may also want to find videos and demos in to things like Word2Vec, google's BERT, and zero shot learning in NLP in general. also look at the e-palm model google just released a demo of. that some of task tranlation is probably your biggest lead

The thing about medical expertise is that so little if it is conveyed through the literature, because of the limitations of text and even images/recordings. Things like symptoms and disease progression have very particular looks and feel that can’t be easily conveyed. Also, the full explanation of what normal and healthy is is also poorly expressed. In your profession, there is probably a lot of nuance to exactly the right amount of pressure to exert on teeth in different circumstances.

If I were you I would catalogue where the literature falls short, and where/how you did gain your expertise, without trying to explain exactly what to do. In other words, tell the developers where they need to focus their efforts.

I agree with your assessment that a lot of what medical professionals do can and arguably should be supplanted by technological solutions with deep and subtle expertise built in. I think besides the software we are waiting on robotics better capabilities, particularly things like sensory feedback as detailed as human skin.

There are so many ways to tackle this, I guess I would start with a use case. Since I know absolutely nothing about dentistry, let me ask the question - what is the absolute dead simple work that seems like it could be automated? Knowing nothing, I suspect that things like teeth cleaning could be performed by a machine for most cases. You can imagine in your home having some kind of thing you stick your face in, open your mouth and a large amount of data is collected visually about your teeth. If there is a way to see plaque and calculus, ML would highlight that and say, “remove?” And you would say yes, then it would gently pick at your teeth, visually inspecting the whole way. You are probably pressing some kind of trigger the whole time, and seeing the machine work the whole time. This is so you have some sense of control and in an emergency you could just release the trigger. Of course this would only work for the standard cases, anything else would need to see a human specialist. Eventually in 40 years no one would trust the human - all use cases covered.

My dentist uses very little new tech, it would seem to me if you could build a robot that could inspect the mouth visually, perhaps perform parts of a cleaning or other repair much faster and more comfortable than todays procedures. This robot could be deployed remotely or even home. Toothache? Buy this robot at Walgreens and a AI will tell you what the issue is(get a human opinion for only $99 more!). Collecting lots of images would let you at some point create a ml model of defects that could then be identified by the machine. While the science of ml is complicated, collection and creating models is much less complicated. The tech is great but this has the potential to solve the real problems and bring automation.

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>Everybody lies.

In medicine, patients often say X but mean Y.

It's not really lying.

As a practitioner, it's your job to drag this info out of them.