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. Hello and welcome, Real Talk. This is your host, Dr. Scott Morris.
Today we have a special guest joining us, Dr. Alex Martin, who's a prominent optometrist and a health tech leader currently serving as the chief medical officer. He's the chief medical officer of Ibot, where he oversees, let's call it the clinical integrity of their rapid 92nd vision testing, he asked. He leads the clinical oversight and the clinical advisory board and he's very instrumental in Ibot's mission to provide accessible doctor verified prescriptions.
He also serves as the medical director of Boston vision and Lawrence Massachusetts, specializing in dry disease, glaucoma and diabetic eye care, as well as a junk faculty member at the New England College of Automatry. We share that Alex and a section editor for the Journal of Medical Insight. So Alex has done lots and lots of different stuff. He's a fellow of the academies, because recently recognized, congratulations as one of the world's 20 visionary professionals to follow in 2025.
By all around the worlds.com. I mean, he's co authored clinical optometry, the Spanish speaking patient phrasebook to improve inclusivity in I care. Alex, let's put it this way. He's done a lot and I'm very fascinated to have him on the show and pick his brain about the future of I care.
Alex, so welcome to the show. Oh my goodness. Well, thank you so much for that introduction. So Alex, welcome to the show.
Super excited to have you on. Oh, thank you so much. It's a pleasure to be here. I'm a very long time listener of the show.
So being here is really good and talking to you is great. So thank you so much for having me. Thanks for the opportunity. Well, this year, welcome.
This will be a lot of fun. For the audience, you guys know whether we have guests or not, Ray, I was trying to include a little bit of a knowledge bite where we break down some of the terms and tech shaping our world into single digestible information. And so today we're going to talk a little bit about diagnostic AI and I care. So what exactly is it?
Well, diagnostic AI is essentially a super powered. Let's call it magnifying glass for your eyes. It uses deep learning algorithms and these systems can scan thousands or hundreds of thousands of high resumous images of your retina, your optic nerve and soon your entire segment in mere seconds. Well, the human doctor is incredibly skilled.
I doesn't get tired and it can spot patterns. Tiny changes in blood vessels or in her fibola or horneal fibers that are just literally invisible to our human eye. Now, as we always discuss, it's not about replacing the doctor. It's about giving them a co-pilot, if you will, that memorized millions of medical cases and never misses a pixel.
Now, why does this all matter? Because in eye care, time is sight. Right now, AI is still being used for autonomous screening. Let's take diabetic retinopathy.
In New ASI AI systems can diagnose this in primary care clinic, clinic soon, even without a specialist in the room. And this means people in rural areas or underserved communities can get life saving diagnoses through a routine checkup catching the disease years before symptoms even start. But the future is where it gets even more exciting. By the end of this year, and as we look into 2027, we talk about this term, oculomics.
And since the eye is the only place in the body where we can see blood vessels and nerve directly in real time, AI is being trained to learn to use ice cans to predict systemic health. Now, we're talking about routine eye exams that can potentially flag your risk back, flag you as a risk for heart attack or stroke or neurodegenerative disease like Alzheimer's, years or maybe even decades before they manifest elsewhere. It turns out the eye exam and with the use of diagnostic AI may just be the true window into your entire body's health. AI is not just about faster prescriptions.
It's about democratizing health care and moving from reacting to vision loss to preventing it entirely. That's your knowledge bite for the day. Hope you all learn something. Alright, so Alex, when our pre-meeting, we were chatting a little bit for the audience, we were chatting a little bit about what some novel concept we might have.
And Alex, he terms it up, Tomatry 3.0 and Alex were kindred spirits in that one. I love that term about I call it the next evolution and what it's going to look like. Tell me a little bit about what you're thinking when you say the words of Tomatry 3.0. Well, that's that's that's excellent.
So a couple of things I cannot take credit for optometry 3.0. The first time I heard it was from Reed Fawze on LinkedIn and that his post really inspired me to keep kind of hammering away at the idea and molding it and figuring out, you know, how do how we're going to actually make this work. I'll give I'll give a quick summary of kind of like what we're thinking when we say optometry, you know, 1.0 2.0 3.0 and and where we're going and actually at the end, I'll even put a little bite here that I think we should probably even change the name from optometry 3.0. So we should we should change that maybe.
I think it should be I care 3.0 exactly what I'm saying. I don't know. I don't know. He's left out.
It's not just right. I need to say it's ophthalmology. It's optics. It's the industry.
It's a whole team. It's a whole team about where we're going in the near future. Yeah, yeah. So for those that don't know of kind of like these concepts, optometry 1.0, we think of that as the origins, the vision correction era of optometry.
So that's like the late 1800s through the mid 20th century. That's a focus where optometry is just, you know, really refraction dispensing lenses for glasses and then eventually contacts, but the optometrist really the role was, you know, technical provider of measuring refractive air and then supplying the correction for that. So the technology that this person had was limited. You know, we don't have they didn't have access to everything we have today, but manual refraction.
Really just like rudimentary ophthalmology, yeah, ophthalmoscopy sorry. And the scope of practice for the people practicing at time was very limited. There were just no diagnostics. You didn't have the ability to dilate someone and take a look at the inside of the eye.
So very different from where we are now. Yeah, that's just that's the patient just coming in getting glasses leaving and that was that was it. So optometry 2.0 we think of that is where optometry schools are teaching us now. You know, we will let's think of ourselves as medical I care.
So that's expanding into medical management. That's where we are considered the primary I care provider. And that's managing ocular disease that's having the ability to do therapeutic drugs, co managing surgery. And taking advantage of all the technology that we've all gone really accustomed to, having OCT and and fundus imaging, corneal topography.
Everything that we enjoy now. So the scope. But I think Alex, you know, I, I, I, I'm going to cut out there and I think about that I was talking with one of my student docs the other day and I started thinking about when I was their age forever and a deck couple decades ago. And I was the very first, they called it the NFA the neuro fiber analyzer in my residency.
We had the first, first one of the first topographers in the United States in our office in my residency location. I thought I was just cool. Now I look back and go, oh my gosh, that was barbaric. And so we talk about all those new cool technologies we have today.
And I go, you know, in 25 years of these students going to look back and go, can you believe we manage things with the OCT and a perimeter or a ton log, you know, a tenometer. Can you kid me? It's fascinating to think about if you fast forward another 20 years. What that change will look like.
And I think it's going to be much greater than change was in the last 25 years. I'm all I completely agree, completely agree. Every time I do like a dry innovation lecture series and you just you go from all we had was restasis for forever. And now every year we've got two or three drugs in the pipeline and it's it's incredible.
When Paul and I he was on, he was on our innovators podcast a couple weeks ago. And we were talking about because he and I were the first ones. Oh my gosh, literally 30 years ago before restasis even came out when we were prepping for it, you would say. And we were in competing practices across the street from each other in Kansas City.
And we were like, we're going to make this dry thing. People like, why would you talk about dry eye nobody's got that. And now I look at the technologies we have to treat that or to a diagnosis and treat it. Wow.
Right. So, yeah, that's crazy. I think how far we can just dry practice. And yet how far we have to go.
Absolutely. 100%. Alright, so I cut you off on where we're at in 2.0. No worries.
No worries. 3.0 is going. Yep. So 2.0 is we've already kind of covered and that's where we're all really familiar with now.
And if we fast forward to optometry 3.0. So this is basically from now forward of how do we figure out how to make really personalized. I care. But the challenge is not just personal.
It's personal at scale. And it's, I mean, the role of the optometrist is going to be tech enabled. As you and Ron talk about all the time of, you know, how are we going to be able to interpret the AI for our patients. How do we explain what's going on.
And we're going to be able to take all of this data and information and put it into a chunk that they can use and ultimately get to the point where we're preventive and not just in the cure state. So really trying to proactive versus reactive. Yeah. Exactly.
Prevention, predictive care. Making sure that we're becoming almost like continuous. We can analyze that much continuous data is probably through the use of AI. Just too much data for our little gray brains to build to process.
And that's what we've talked about many times. And for the audience, you listen to knowledge bites. This is a recurring theme is. It's compute power, but it's pattern recognition is just far superior to us.
But I think I'll actually get a really good point for I care 3.0 is we will become the points of connection between the data and the delivery. And I just, that was cool. I think that's a great phrase. I should say that one.
You know, is that are we as we look to the future. Do we need to retrain re educate. The way the language right that we're using and how we're interacting with our with our patients and I'm curious your thoughts on that. Yeah, no, I completely agree of I think scope of practice is going to be huge of how we regulate that manage that.
The expectations that are placed on us as eye doctors and how we can coordinate almost as like a panel of doctors to be able to take care of patients. If we eventually achieve being able to communicate not VFX. And we can communicate much quicker. You could coordinate care much more effectively.
That actually. The technology from the 1970s. That's just insane. Because it's more secure than cyber tech.
Exactly. Right. Yeah. It's just because it's so in the dark ages that nobody can read it.
Right. Right. How much can you really communicate through facts? Well, I would say how much can you communicate through an EHR that's static and a bunch of check boxes, right?
We're not we're not doing flow of thought. We're doing. How many boxes can you check that we're actually relevant and true? Right.
So. Oh, we'll talk to me. What. So what do you think it looks like?
I mean, you know, there's obviously give me the big picture. What do you think looks like a decade from now? And then we'll break down. What does it take to get there?
You mentioned Paul. So if, if you know, Dr. Carpeki has. The practice with the most showgreens patients in it.
And I, I see a ton of showgreens patients. But let's say that when I was first starting and I hadn't seen a bunch of showgreens patients. AI would elevate me to being able to see what were Paul's patterns to figure out what's the best way that I might be able to care for a patient. And then I think that's what I think it's going to be.
I think it's going to be a great way to be able to level the playing playing field. It also be a huge advantage. I agree one example of 3.0. Yeah, we have this term, you know, we're going to make the rest as good as the best.
And that's what AI will be able to do. It will literally make every. It will level the playing field in terms of cognitive knowledge, maybe not in terms of delivery. But at least in terms of cognitive knowledge.
And I think that's a great way to get some tools potentially to think about our angles I hadn't thought about or. Likely outcomes that I hadn't considered as a, as a new doctor compared to to know. Fascinating, fascinating. Okay, so that's, that's the diagnosis part, right?
And I think we, you know, we talked about the knowledge by diagnostic AI. It's not just going to be a calomix. It's not just going to be an OCT or, you know, be able to scan coenial fibers, coenial collagen fibers or something like that. It's also going to be how do we think through it?
You know, how do we deliver care more efficiently because we don't do tests we don't need to do. And make sure we do the test that we should do. So I think diagnostic AI, when we look at that section of care delivery in terms of I care 3.0. I think that's interesting in that we're going to definitely have the diagnostic capabilities of the best at our fingertips.
I agree there totally agree. Talk to me a little bit about. What does the treatment look like? Like how does 3.0 change the way treatment works?
Yeah, I think this, like I said, this actually happened to me about a week or two ago. So I have residents that come primary care residents that rotate through and kind of get a taste of optometry and ophthalmology. And we actually had a patient that was recently diagnosed with syphilis. And it was interesting to figure out, you know, what their concerns were, why they were in the room.
What was, you know, where do we go going forward? How do we make a treatment plan to be able to see them? But it was perfect because the primary care resident that was with me had access to their chart and could pull up exactly when they were diagnosed exactly how many injections they've received. And so we could actually build our plan as primary care and optometry going forward.
And so the patient left being like, wow, like you guys are on the exact same page. I know I can go to one person. You guys are going to talk to each other. And that was just a really cool moment.
So I think that that's more of what optometry 3.0 is going to be able to make for us. In the future when information is truly integrated across all of medicine, where we all have not. Let me look at that EHR and then I got to call somebody get that EHR. We got to analyze that when it's all just right there, everything.
Any guys are doing the interpretation going here's the big points, right? I think that's a decade away at least. And there's a lot of political challenges of getting EHRs. The co-op share information connection.
There's a lot of hurdles. But boy, the light at the end of the tunnel is a beautiful big. The promise is there. The promise is there.
The promises there. We talked about it a couple of weeks ago. We talked about a couple of weeks ago, democratizing care. You know, that's the goal.
That's that's the goal. There are hurdles without a doubt, but there's it's the goal. So, you know, once again, is when you can start collecting data from everybody, demographic looking at phenotype genotype as we always talk about. I mean, oh my gosh, that's insane.
What we might be able to figure out that some treatment that only you are using might help people all over the world for certain phenotype genotype that nobody else. It take me a decade to see enough people and put it together if I'm paying attention to get all that right. I mean, I just think they truly the democratizing of what works best for every phenotype genotype. And having AI is patterned be able to see that it's that's once again.
That's the that's the yellow brick road that we're all trying to get to. Well, so Alex, you just talked to me a little bit about we're not doing, you know, we try not to real talk to do commercials for anybody, but you know, you do guys do have some really fascinating technology coming down the pipeline with I bought. You know, in terms of kiosks and my business partner and I we worked on this technology 15 years ago, we were just way too early. So when we think about diagnostics in terms of diagnostic testing, whether it be refraction or in office, we did a podcast a couple weeks ago.
On real talk that we were talking about the future of diagnostic testing centers. Tell me what your thoughts are on that, you know, I. I think most care won't happen in an office a decade from now. It's going to happen somewhere else.
And he asks or and or testing centers. I think we're going to be the key element of that. I mean, when you guys look at that, what do you see is that the possibilities and the challenges. Great question.
So yes, tons of challenges, right, tons of challenges. But I think. Yeah, it's it's there's there's so much here. I know there's a lot to unpack their outs, but just you know, let's think about what the possibilities are.
Let's let's paint the big rosy picture. Then we'll get into that needy greedy details. All right. So rosy picture would be patients would be able to walk in anytime anywhere that's convenient for them.
And I think that's the best way to test it as often as they want to. So what that'll translate to for us is that we're going to start seeing if patients come into our offices with trend analysis. That it's not going to be based off of well, last year, your auto refraction was a minus one this year, your auto fractions of minus three. So I think that took place is their cortical cataract that's getting in the way of the AR.
Like you're making a leap when you first see that patient, whereas if they came in with trend data, you would already, yeah, you'd already know where you want to go with that patient. So I think that's what having these kinds of centers would do for us. And then you tie that into you know, I mean, I think that we have a podcast of coming up here that I've already done come I pre talked with that person about, you know, wearables, and implantals will be soon be able to measure blood sugar, live time and feed all that data. And when we find that, hey, you know, there's a blood sugar here that's been steadily going up and all of a sudden they're getting more myopic and they've had a doctor shift, but that equals, you know, one point change on their hemoglobin A1C.
I mean, the connection of that kind of data is. Exactly. And maybe it'll look a little bit more. Refraction standpoint, right?
Alex says, you know, you didn't say it, but I go, I know you guys got to believe it and be believing it is, you know, I think refraction may be one of those things that goes, hey, we've seen this trend. Maybe we should be watching your systemic issues like blood sugar, like your film, like hormones, like whatever, right? I think the diagnostic technology you guys are having open access could be as or more important than thinking about no CT and what that means for diabetic retinopathy. We may see it sooner than that.
I mean, think about we see refraction changes because a lens changes way before we typically ever see retinopathy changes, at least in our site, maybe with digital imaging, right? We're going to see them decades earlier than that. But I mean, I think that when we look at refractive data for everybody out there who actually uses a foropter and has done a refraction in the last five days, that technology, we use the diagnostic tool to help us figure what's going on the rest of the body. I'm fascinating with where you with the technology you guys are working on is going to go in terms of how many people might it save how many people not just that, but I mean, I think, well, gosh, you know, I can't get if we're going to get your eyes check more often in terms of vision in terms of refractive status.
And hey, now I'm 20, 80 and I shouldn't be driving. It's not just what we say lives of that person, we say lives of somebody used to be on the road. No, that's that's completely valid, but yeah, I could I could imagine a day where you're able to do lens densitometry. That's a good thought and just you would.
Well, let's take two examples. One would be the patient that came in to see you that was previously told you're never going to need cataract surgery by some other doctor. Come in there 20 25, 2030 and you're like, there's definitely, you know, something. Yeah, we can't be up three years, dude, not never yet, but when is the exact time?
How do you quantify? Well, you know, cataract surgeons have a wait list. Some cataract surgeons as two weeks, some cataract surgeons, depending on where you are in the world, that's two months, six months. So, so robotic cataract surgery hits mainstream.
Yeah, that's true. But if you were able to figure out a way to almost line people up based off of lens densitometry. Exactly, exactly. You'd be able to filter a lot better.
Wow, that's a novel concept. I never heard that that's new Alex. I hadn't heard that before that's a. There's two really big big reasons why I'm involved with I want.
I think that being able to quantify cataracts, every time I've done mission trips, that's the most important thing is this cataracts. So that's that's kind of where some of this this thought came from. The second big reason would be credit on us. There's nothing that annoys me more than getting a patient that's in their late 30s or early 30s and you're like.
Has anyone ever told you like why your vision isn't correctable in this eye or both eyes and the answer is sometimes no, I've been to two, maybe two or three eye doctors and I wasn't sure and. I have that point at your you've already lost so much time. So being able to make devices that would be capable of helping doctors make these calls is that that's that's my mission is. And maybe remotely you know, I've said before the show I have a mission clinic down in Wore as Mexico on the colonies and I agree with you I go there and sometimes you're seeing you know we never see a cataract in the United States.
Like one that walks in every two hours in the clinic right I mean you're seeing a grade for horrible you know it's already liquefied more gaggy and cataract or you know care to cone us it's a 55 on the caratometer. And and that's because I am much like what you do Alex you I am the care for the next five years right. And for that one visit and what are we going to do about it right but as I think as you guys are bringing interesting technology to could we automate so much of that so I'm always amazed by how many people in this little colony are walk around as a plus four minus five. How are you how are you operating right I mean they're 60 years old they've had this care to cone us and you know how are they operating in this while head glasses I lost them about two decades ago.
I'm like oh my gosh right I mean here you know and for the audience that you know you guys all those people come in and oh my god my visions were alive change the minus quarter and these people are walking around 2200 getting through life and so you know the technology guys what happens when we take it out of. First world countries we start putting in third world countries and how much of it impact is technology like we guys are working on going to change the global health of the world. That's another big reason why I'm involved and I want to be the advocate for safety patient safety how do we find how this new model is going to work between. You know checking the box for industry checking the box for doctor checking the box for patient.
But I mean you go to some places in the world and if you look at the data there's maybe one to two eye doctors per million people. Yeah and India is one point done the math to figure out how many patients you can see in your lifetime. Yeah I did I've done the math in fact I think we've done this you know so if you're a doc and you're seeing averaging averaging averaging 20 patients a day times five days a week so that's 100 patients times 50 weeks as well take your time off that's 5000 times a 20 year career or 25 year career you're talking 100 to 125,000 patients you're going to see in your lifetime. And yet like you said in India it's one ophthalmologist for every 1.24 million people the math just doesn't work right doesn't want so.
You know in our first world country like here we can complain and be political and go oh my gosh this is you're going to destroy the industry blah blah blah blah I'm all that political BS but the reality is for anybody is arguing that go take a trip. Go see what the rest of the world doesn't see that's changing your opinions you you said it I didn't but yeah I mean that's that's that's a total of every million patients never afraid to share my opinions on stuff so. But it is only thousands of doctors how do we fix it. There's no need to be there's no need to be territorial we all need to recognize that.
In the next 10 years like you say it's what is done it within our four walls will change we need to figure out how to regulate that we need to figure out how that that still is profitable to keep our practices going. But I don't think the answer might not be done in our four walls Alex it might not be done in our four walls and that's the that's the facts that our industry needs to embrace is I believe that I care 3.0 won't between between the four walls of an office yeah I completely agree we just we have to do responsibly of course everything that we're going to be doing has to have been clinically validated of course. But if we're able to free up our time free up patients time ultimately see more patients provide more predictive care what's the problem there. Well so what are the challenges but you know what what when you look at this and obviously you think about this every day in a totally different context than I think about every day.
So what do you look at go man here the let's never down you know what's the big three to five challenges that diagnostic AI has in front of it and you mentioned validity and I say validity versus bias yeah I totally agree with that but what are some of the other like you look at the go man this is a big hurdle. I think big hurdles would be and I think other innovators have talked about this and that's. I think everyone's come to the idea of how do we open the data how do we I think I think you'd have to solve this by making a clinic with the intention of telling patients hey this is a clinic that's that's going to be used as a library for the future and we're going to scan you with these six technologies and. And you're going to get paid to be a patient like I think that's a key to if you're being a patient that's creating the library you should be paid for that.
And you just you make three three of these centers around the country the patient gets scanned by every technology that's available and you track outcomes for 10 years 20 years 30 years. Now you've created a data set that's not just based off of how did one doctor code and an EHR 20 years ago you're going with the intent of creating really good libraries. That's an awesome idea so that's how you'd actually have a podcast that's a. Well you know it's funny I you know Alex you say that you know and it's funny because tonight we're going to record Ray on our comporting doing another real talk here for probably the one after years and we're talking about digital twins and how we can use digital twins to train the models but you come up with a real live model and maybe we can play compare the virtual twin model versus your model 10 years from now to now and but the way wow that's a fascinating idea.
The way the way forward really is not just we're going to go back through the data and simulate what would have happened and we have this I think we just we all agree on making these actual centers the patients are all aware and that way it's all signed off on the patient gets paid to be a patient and now we have a real library that's open source. Brilliant. You have to put of course too you can't just put these in one kind of area. What let's try and go for 10 clinics let's put them all over the place let's capture as much diseases possible people of all backgrounds truly democratize care.
Yeah I mean don't let's not just put them in an urban center or rural center let's spread about maybe not just in this country but all countries that's not that's a really yeah I mean I got all over the place. Think about like top con or S. lore or you know you look at those groups and go they have their footprint all of the world. I mean just that the pod that you bring to seco put the pod in Atlanta and leave it there right let's just get data for a year.
I got some sales to do Alex to get that to happen but I love that idea that's crazy anybody in the audience if you guys are like hey I love that idea you know I. Let's talk more about that we might actually do a little round robin on that one and have some other people on board and get that that's that we can give legs to that that's a great idea. Yeah so I think that would that that's the only way I actually see it going forward is. If you go if patients are informed from the beginning.
And most patients are transparency of the patient I'm like hey transparency I've got I've got a kiosk here it's in research and development it's gone through regulatory processes it's FDA regulated are you willing to be a patient for it. The answer is almost always yeah sure of course I'd love to be a part of that. People want to help the greater good they always do everyone's interested if they don't do the rare burden. Yeah absolutely yeah I don't want to slow you up at all please.
Exactly right Alex that's the best idea I you know I was trying to keep these around 30 minutes just so the audience doesn't get bored but man if we didn't leave you audience with a great novel thought about how to change the world. Alex that was it right there I mean I like I'm 23.0 or I care 3.0 and all the stuff we talked about but man the library of the future of that's amazing thought. There's contributing to the future of the world Alex you just did it man you just did. Thank you so much I would also like to leave one last comment of the technology we're making is always doctor reviewed it's not an a i kiosk.
All it's doing is being our data gather the doctor is still involved in making any decision that goes through that kiosk. Awesome for everybody this was real talk with Alex Martin from who's the CMO at i by. Hopefully you learned something hopefully Alex and I made you think about a few things that you do every day and you accept his truth. Maybe it's just a little bit fiction hope you learned something today Alex thank you so much for your time thank you so much for having me.
You've been listening to real talk an AI and I care you're weekly podcast to keep you informed about AI technologies revolutionizing I care.