This episode of Real Talk from AI and I Care is brought to you by Barty Software. Welcome to Real Talk on AI and I Care with your host Dr. Scott Morris. And I'm co-host Dr.
Rehan Ahmed. In each episode we discuss current news, adding a little AI education, and debate innovative AI tools and topics that will change the industry. Fun show today I know you're going to cover a little bit about some exciting things in the news, and then I'm going to kind of talk a little bit about what is an algorithm. We reference that all the time and maybe sometimes we need to define exactly what it is.
And then I'm really looking forward to you and I've had many of these conversations about remote diagnostics and how that's going to affect what we do. We're going to spend a few minutes talking about that. So, Brad, fill me in. What's the news of the week?
This episode of Real Talk is brought to you through the gender-responsive ship of Jopson Publishing, Publishers of the leading sources of information in the I Care Space. Well, interesting, exciting news this week. Both pieces of news have to do with a company called TopCon, which I'm sure everyone here is familiar with. So, TopCon made two investments this week or two partnerships announced them.
The first one was with a company, actually, I've never heard of Scott's called Machine MD. It's a Swiss-based company. They do diagnostic headsets, but not with, they do some visual field testing, but the real area of expertise is in neuroophthalmology or neurooptometry. So, neurologic testing.
Well, that's an interesting purchase. Yeah, it's different. I think Opulomotor analysis, diplopia, pupil assessments, and they do also do visual fields, but they are really going toward the neurologic standpoint. We always talk about the I.S.
Relipicalized, especially for TopCon. Yeah, it's interesting point from them, but on the other hand, it makes a lot of sense because, as you know, they have this full healthcare from the I initiative that they're working on, and so they're looking at the cardiac stuff and they're looking at neuro-neurology from dementia or Alzheimer's, and now they're going into more of that. So, it sort of makes sense, but it also relates to the second news story, which also involves TopCon, and that's with a partnership that Glocos had with a company called Radius XR, which again does headsets, so this is a theme here, and they've entered into partnership with TopCon to be their exclusive distributor. Details of the data.
Radius XR has. What's that? Radius XR. Radius XR.
So, Radius and Glocos were in partnership already, and now TopCon is being the distributor for them. So, again, it's the partnership. So, I wrote about a couple of weeks ago in the journal on the value of partnerships where you have software companies, hardware companies, companies that are going to act like an app system for the ecosystem, which is what Harmony is, which is from TopCon. So, it all sort of makes sense from that standpoint.
What's interesting here is that they're both headset companies. So, it's clear that TopCon is very interested in the headset space, the diagnostic headset space with the space. I know this is something that you talk to Heuroo about this week. So, and what does it have to do with AI, right?
Because there's not an obvious direct connection, because these are headset companies that do diagnostic testing on visual field or pupils or color vision or visual feuds. The connection in Scotland, I know you would agree with this, is that it's all about the data. And as these devices get smaller, and you take them home, patients are using them more often, they're going to have integrated AI systems on them, or they're going to communicate with other systems that will use their data and other AI systems. I totally think and I'm sure we're going to get into that later when we talk about remote diagnostics, but I look at everything as basically a sensor, right?
It's no different than our senses. We have our fingers, you know, kinesthetic, we have our smell, we have our vision, we have our auditory. We have a lot of sensors that are out there. They're going to be feeding data into algorithms, kind of a transition, what I'm going to talk about, but into algorithms and those algorithms are going to use AI to change the way we deal with data.
Oh, absolutely. And so, this is, I think we're going to see a lot more of this. We talked a couple of weeks ago about how SLOR is building partnerships and here, another large company like TopThon is working with smaller, in some cases smaller companies, in some cases larger companies, Galcos is a big company with radius. And so, this is again really interesting, or I think we're beginning endings.
Eventually, I'm not sure how they had set spaces going to pan out if all these competitors are going to survive or not and what the landscape is going to look like, but definitely very interesting. I think overall, a great thing for clinicians, because we'll have a lot of options and decide which best for us, our practice and our patients. Cool. Well, I'm going to kind of hit on a little bit like our, we always try to cover basic science, right?
So kind of getting our audience up to speed with some of the terms that we use. And today we're going to talk about algorithms and we kind of toss that word around a lot. And, you know, algorithms are really just, they're essentially a mathematical program that's used to teach a computer how to learn and maybe someday even operate autonomously and maybe even now we can use that word. And, you know, these algorithms, they come in lots of different ways.
And I'll kind of break down different versions of those. But in a nutshell, they're you, they use data that can come from all kinds of different places to identify patterns and, you know, predict kind of what's going to happen or maybe even some of these days make decisions about how to perform tasks. And, you know, we already see some of these algorithms for natural language processing or image recognition or even playing games. I mean, there's algorithms everywhere and the algorithms are not new.
They're not new to AI algorithms decision making in terms of what we all learned. And, you know, in school is an algorithm of how you deal with this or when you see this, you do this. They're linear decisions to linear is kind of becoming more 3D. And before I get into that, let's talk about there's really kind of three major types of AI algorithms.
There's algorithms that take data that's already labeled and they make predictions or classifications that's been sent to someone else to supervise. And, that's called supervised learning algorithms. And that's traditionally what many of our algorithms are simplified algorithms have been. And that's kind of a lot about what we see right now.
But, we're in there's enough is we're starting to get into an area of the second type of algorithms, which is called unsupervised learning algorithms where they learn from data that's kind of vague. And maybe just think about thrown all your data in a big pot and they go through and sort it and figure it out and discover and see patterns and structures that maybe we weren't able to see. Whereas supervised learning was saying, hey, we kind of know this and can't it do it better than us. But there was a set data trail with unsupervised learning not so much of a data trail.
Kind of a melting pot, if you will. It's, I think of it as data soup that the system then goes in and pulls out the particles of soup and says, okay, let's make something. And then there's kind of, I almost feel like it's something kind of in between where you take what's called reinforcement learning. And this is where algorithms learn through trial and error, meaning that they go down their algorithm and they say, okay, here's my answer.
If the answer's right, they get a reward and they stick around. And if they're not, they're penalized. Boy, that sounds a lot like rearing children to some degree. You know, it's, I mean, kind of think about that and go, wow, Ryan, isn't this how we taught our children?
So you're saying our kids are just algorithms that we just need to do reinforcement learning on. I'm sure my son's listening right now would go, yeah, I can remember when dad used that philosophy, right? But maybe it is. Maybe AI algorithms really are, and you were talking about where's all this going to go with some of the technology.
I think we're still, I think maybe we're leaving the infant side of what we're doing. And maybe we're now we're getting into the toddler or the preschooler area, area of AI in medicine. But maybe we still need to teach it a lot. And I think there's a lot of it out there.
And you know, I mean, when you talk about algorithms, they break down into lots of different things. You can use them for like decision trees. You can use them for clustering. You can use them as what we really talk about is neural networks, which is kind of how does the brain structure and function work?
And that's where we go from linear type of decision trees to neural networks, which you take a series of stacked linear decision trees. Like, think if you could think of a 2D decision tree that you write on a paper and now stack 100 layers of that and now start connecting these 3 dimensionally and a vertical axis as well. And maybe even a 3 dimensional axis, not just vertical but horizontal XYZ. And maybe even another axis of looking at how these neural networks work.
And so algorithm themselves, and I've really been involved a lot in the last couple years, they are fascinating all the different types and the different way we use them. So hopefully you guys get a little better understanding of what an algorithm is and maybe some different types of algorithms. So when you hear the words, well, this is supervised or this is unsupervised or this is a neural network, you understand these are all just really rule based systems that help us figure out how to learn and how to see things like pattern recognition problem solving. So they get more and more complex, they get more and more interesting, but as they do, they also get better.
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And I know we are going to talk about remote care now, which I know is a topic near and dear to our hearts. So tell us what you found out. Well, you know, so we've been talking about remote diagnostic testing and I think there's, there's, I want to kind of break it into two parts and we kind of talked about this a little bit last week and then I also talked about it a couple of my innovator series about remote diagnostic technology is not just, oh, let's go put a kiosk in some remote place. And though that's definitely an option, right?
I mean, we talked about, I think last week of, you know, I'm the last eye care provider for about an hour and a half to the west. It'd be nice to have people not have to drive an hour and a half and have a remote diagnostic technology kind of kiosk to pull in data and then do it kind of via telehealth or virtual health. I think that'd be a really cool idea and I think that's one avenue of remote testing. But I also think you could think of it.
Maybe a little more futuristic, but do all of us really need to have all that technology in every single office? Or will we see remote testing centers, almost like MRI centers where you go have an MRI and then it's interpreted somewhere else and I kind of wonder if our practices won't someday morph into something like that. And then I guess there's a third category you put on is and we're all wearing it. You know where you're wearing our urinary or apple watch or you know heads up display.
You know, I mean, we look at all the technologies we've been talking about with what, you know, virtual reality augmented reality, I wear is going to look like maybe remote diagnostic technology is going to be something we wear, not somewhere we go. And you know, we're talking about headsets early on. Maybe that's the first step into true remote diagnostic technology. It got granted.
I think we're in toddler phase, but you know, I look at then go, I think there's three that maybe falls under three different terms. That's my thoughts. I mean, I don't know. What do you think?
Yeah, I think what you brought up, because I've always been shocked by going into various ophthalmologists and optometriopists and really being over in all of how much technology we all have. And the thought has crossed my mind that isn't this kind of redundant that you know, I have no CT machine, I have a visual field machine, I have a fun to scan my, I have all these things down the street at the next ophthalmologist or optometrist office, they have the exact same stuff and block it. And so I wondered when you go see your orthopedist or your internal medicine doctor, they don't all have cat scan, they don't all have MRI machines. And I've wondered the same thing too.
And as eye care imaging gets more advanced and more expensive, one wonders whether this is a sustainable model. And I think the idea of it being a remote care, it sort of fits in really nicely with that concept too, because if you, if you abstract all the imaging from the patient and some of the diagnostic testing, which we talked about last week, like the SLIP lab, then you could have just a regular face-to-face interaction virtually anywhere. Anywhere. And have all their diagnostic information, just like you would if they were in the exam line with you.
You know what I mean, I think, I agree, and I think that this is, we're at the precipice of a major evolution, we talk about this almost every subject we, one of these do, I think we're at a major evolutionary shift about what our offices look like and what offices where offices are. You know, I mean, I think that remote diagnostic technology is going to change, I mean, obviously it's going to great, it's going to bridge lots of different geographic barriers and maybe allow specialized care in lots of different areas and give people who have, you know, I think about a lady I saw yesterday who she hasn't been able to leave her house in six months, right? This was her going out and she's doing all of her medical appointments in one day because she has a ride and she's in a wheelchair, she's confined to wheelchair and I think about, you know, I mean, fortunately she didn't have anything wrong in our world, in the I care world, that was great, but think about those people, maybe now they can see care for those people who don't have transportation, you know, and maybe that's going to be those heads-up displays and we think about remote, you know, I mean, tracking what their vital signs are, maybe not so much in I care, but, um, or maybe not, you know, we talk about some of those devices that are going to be implantable IOP sensing, and I wouldn't even say IOP, I don't even know if that's the right word for it, but IOP sensing devices, I mean, maybe glaucoma is going to be a totally different game when much like you, you know, right now you have a remote, if you want to think about remote technology, you have our diabetics sometimes have monitors on their skin or whatever that are feeding continuous information or your ur-arrang is going to feed continual pulse-ox readings or whatever, you know, I mean, this patient monitoring, think about what we'll find out when we're actually looking at glaucoma evaluations, you know, intra-ocular pulse amplitude and IOP and blood pressure and how those things work 24, 7, 365, now obviously that's a crazy amount of data, but AI can help do that, I think we're going to find things about glaucoma because of remote diagnostic technology, we never even conceptualized as being possible. Yeah, so my prediction for the future is I think the in most meaningful remote diagnostic for IKARE is going to be homeocity when it's on, there are several companies like Total Vision that are working on this.
I think that's the lowest hanging through because these are elderly patients who are coming into the office every four to six weeks or eight weeks depending on their treatment protocol and if you could save them a couple of visits and save them coming in and potentially with longer acting agents they may be staying at home longer and knowing exactly when to come into the office that would affect a lot of patients at a high dollar value and so I see I see pairs, I see patients and providers all sort of coalescing around that, to me it makes a lot of sense. I think glaucoma too makes a ton of sense with these, almost then I think your analogy to continuous glucose monitoring is a good one and in terms of thinking about how we would could monitor IOP because we don't really have any idea what it's like outside of the office which is just three or four times a year. So those are two things where I think it makes a ton of sense and really excited about those companies that are as they commercialize their technology. And I think you hit on a big piece right?
I mean I think that the reduction in healthcare costs in terms of I mean the cost savings of being able to track people and say hey you're having a change or not having a change. I mean yeah maybe the technology is going to be initially a little expensive on the front side and that's maybe one of the negatives I'm sure we'll get into in a minute but you know I mean the cost savings for the healthcare system over for chronic disease I don't even think we can put a dollar sign on that because I this thing gets too big but I also think it changes remote diagnostics and especially wearables and the ability to see wearables that changes maybe the most important thing in my mind is that now patients can be more actively involved in monitoring their own health you know and being able to see that hey I do this and this happens right and I kind of branched really in diabetes and you think of what continuous glucose monitors done for diabetics diabetics now are like oh well hey I eat this food and this happens and they're getting more involved than they're taking better care of themselves and I think that you know I think about not just IOP and they feel if I care but I think about dry eyes like what happens what with the tear film in certain conditions right what happens when I wear my context too long what happens when I spent eight hours on a computer what happens to my tear film osmolarity I mean I think that remote diagnostics going to change the way people take care of themselves and maybe that's a good thing maybe they rely less on the medical system and more on themselves finally so yeah I look forward to it I look forward to the RRing and smart glasses and all sorts of things telling how unhealthy I am so it's exciting future Scott to be to be looking into that and looking forward to discussing all the new technologies in these coming weeks what cool at rayon is usual really exciting and just in conversation love having it with you hope you all have our audience you guys are listening to this you've learned and maybe think about a few things about what the future might look like say tuned we look forward to having you next week we would like to thank birdie software for supporting this episode of real talk for may i and i care