Welcome to Real Talk on AI and I care with your host, Dr. Scott Morris. And I'm co host, Dr. Ray Han Ahmed.
In each episode, we discuss current news, add in a little AI education, and debate innovative AI tools and topics that will change the industry. So Rand, kind of Phil Sandler, it's a little bit of the news in the week going on. Yeah, fantastic. It's always, it's always busy, always interesting.
So what I want to talk about is just a week ago, Eslora announced that they are purchasing a company based out of Canada, a small company startup that makes wide field, the fund is imaging called CellView Imaging. And this is on the heels of Eslora buying majority stake in Heidelberg last year, which of course makes those high quality OCTs. And the question, you know, I have for you is what's the bigger play here? And the thesis I have is that, you know, AI diagnostics relies on high quality imaging.
And all the stuff that we're talking about the AI can do in our journal, especially with regards to disease detection, cardiovascular detection, neurologic detection, it all depends on high quality data, high quality imaging. So one thought is that this is a strategic decision on their part to get as close as possible to the data. And I think they're already vertically integrated, you know, as you know, in terms of other diagnostics and ICAP providers and a very large network in addition to the, you know, very well-known optical side. But what are your thoughts, Scott?
How do you see this? And what does it mean for the industry? Yeah, well, it's funny. Well, I just got back from Vision X Boise a couple days ago.
And as I was walking on the exhibit floor, there was one thing that was very obvious. It was very much a technology meeting. And as well as the exotic, there were very few things about lenses and frames. It was about their technology.
And that was, you could say the same thing about VSP and their booth. I totally agree with you. I think it is about data and to get vertically integrated, it's not just about practices anymore. It's about, do you have the technology to gain the data?
I totally agree. Yeah. Unfortunately, I was not able to make it to Vision X Boise this year. What other technologies did you see that work or second change in for you?
I'll tell you what, Ryan. I saw one of the coolest technology I've been seeing in decade. It's by a company called SLIT LED. And it's an autonomous SLIT lamp.
And I really, I got that. I went back to the booth three times because I was so excited about it. And it made me kind of realize that the way we've provided care and the limiting step being the doctor having to look through the SLIT lamp, I think that the workflow might just change when that type of technology comes out. I think it's revolutionizing the way we're going to provide care.
Yeah. The SLIT lamp is one of the things that so far, and most other doctors I talked to, is a one piece of technology that made you come into the office type of thing. And it's been the same technology for the past 100 years. I mean, it's amazing.
It's a great instrument with incredible optics, but it's non-digital. I guess until now. And so I think as we continue to digitize the patient journey, this is yet another thing that can be used. This episode of Real Talk is brought to you through the gender-responsive of Jopson publishing.
Publishers of the leading sources of information in the I Care Space. And the big talk was AI. Everybody of course said we have AI, we have AI, we have AI. And it got me thinking, does everybody really know what AI is?
So that kind of brings us into the basics of AI, what we want to do is a little educational piece every week. So people who can get familiar with what some of these topics and terms mean. So I think if it's okay with you, and I'm going to do a little explanation on maybe what AI is. Well, artificial intelligence, or often furtos AI, is really a group of technology that simulates human intelligence and machines that are programmed to think and learn like humans.
And unlike traditional computer programs, AI systems can analyze data, recognize patterns, make decisions, all with really minimal human intervention. And at its core, AI relies on algorithms that process vast amounts of information, perform tasks such as speech recognition or image analysis that we just discussed or problem solving. And at the heart of AI is machine learning. And this involves algorithms that learn from data, improving their performance over time without really being explicitly programmed.
Now in healthcare, we're constantly dealing with these massive data sets. So as much data as we acquired and interpret, much of that goes untapped. So AI is a set of technologies that is going to allow machines to learn from this data. And think of it as a way to automate very complex pattern recognition challenges.
And AI is really revolution diagnostics right now by analyzing medical images and patient data detect diseases earlier and more accurately than ever before. And I care is definitely at the forefront of all these predictive diagnostic tools. And though while AI offers immense potential, there's also some ethical and societal concerns such as privacy and bias and algorithms and really the future work, which we're actually going to talk about here in a few minutes. I just want to remember AI is a tool, it's a series of tools and they're powerful ones that can be used to improve the lives of our patients and even us as individuals.
And I think that as this continues, we're going to innovate and the impact of AI in our daily lives and industries will only grow shaping the future of technology and really society as a whole. So that's a little summary and I hope you found this brief explanation helpful. We're going to dive into many, many of these topics every week and go into deeper detail. All trying to do it 90 seconds or less on every podcast.
So Ray, and I asked you, what do you think the future looks like and how is the agonist affect us? So I see for I care professionals and truly for healthcare professionals at large, three buckets. The first bucket is sort of the administrative or operational bucket. The second bucket is clinical decisions of board or diagnostics.
And the third bucket, which is frankly where we probably have most work to be done, is treatment and sort of pharmaceutical support in terms of actually taking care of patients. But the first bucket is the low hanging fruit. And this is where I think there's a lot of operational friction that AI will support. I think ambient scribes, I think insurance preauthorizations, there are already a ton of AI technologies that are going to help with that.
And even like assistance for appointment scheduling and you know, insurance claims processing and like you said, ambient, you know, ambient scribes to help with documentation. I mean, I agree. I think that's the low hanging fruit. And I think we're going to see that really quickly.
And I don't think it's going to replace anyone. I think it's going to allow people to stop doing the tedious machine work and let us be humans and do what humans do better, which is provide care. So then you talked about, you know, the second bucket, which is kind of clinical decision making. And I think that's the really exciting stuff that's coming out and definitely it's early on.
But why don't you talk, talk to us a little bit about some of the diagnostic stuff you think is good to do. And I care, yeah, and I care in particular, we have so much imaging that we're inundated with OCTs, funders, photography, ERGs, et cetera, et cetera, et cetera. Well, and now we have anti-access lamps. And now we have anti-access lamps.
And it's going to, it's going to increase. And so the idea of having multimodal AI. And by that, I mean, an AI that can look at not only the clinical history, but all sorts of imaging of a patient and groups of patients even identify, you know, lesions on a fundus photograph or parts of the OCT and give diagnostic, this diagnostic probabilities super exciting. And I think that's where a lot of energy is being spent and would be a huge win for patients and providers.
Yeah, I mean, I think what we talk about, you know, predictive diagnostics are seeing things that we as humans can't see yet, because we can't recognize the patterns. And how much that's going to increase the precision of what we do diagnostically and enhance how we detect disease? I think it's crazy. And then that only kind of leads into that next phase you talked about, which is, how is it going to affect treatment?
And as you said, I think that we're really still very early in that piece. But I mean, we already see stuff like robotic cataract surgery. And you gave a great talk at Vision X, but West last year about that. I mean, talk to us about where you think treatments going.
Yeah. So your example of cataract surgery using AI to assist with parts of the surgery, like the caps are rexis, or even before that lens calculations, having AI determined which is the best intractor lens for a patient, huge possibilities and opportunity there. As well as in terms of treatment, we had a great talk with Ronia, which we'll be publishing hopefully in a couple of weeks, on this concept of digital twins, which is, and I don't want to steal her thunder in the talk there. But imagine a patient comes to you with glaucoma.
And you could with AI basically determine a number of different paths that a patient's going to go on through their digital twin. Either as it drops, is it SLT, is it a mixed procedure, is it something more invasive? And then with the AI, I can sort of tell you how the patient is going to do on each of the various paths that you are contemplating. And maybe some of you are not in contemplating.
Not that it's going to make the decision for you, of course not. But with you and the patient talking together, you can have a more informed conversation. I'm super excited about that. And it's not that kind of brings along to the other part that I get really excited about.
How it's going to change how we educate patients, our staff, really ourselves. I mean, I think AI has got some, when you think about AI can test what you know, remember it, keep retesting it. I think education is going to be just as an important part of treatment. From ranging from compliance to, you know, how you study for the boards, to the way universities teach.
We have a great podcast coming up with Dr. Priscilla's at the University of the New England College of Optometrist talking about what AI is going to do for education. I just think that the treatment piece of this is just so massive. Though we're still early on it.
And I think the end result, you know, if you take the result of those three buckets, I think what AI is really going to do, it's going to enhance the entire experience, not just for the patient, but for us. I mean, I think I look forward and go, when we can really, truly just be caregivers and not be worried about all the other stuff that is sucking up our energy and our ability to do our job, that's where I think AI is going to make life so much more exciting. It's not going to replace us. Like I said before, it's going to augment us and I see it is making our lives so much more fun to be healthcare providers.
Yeah, I think that's, that's what I'm going to promise. That's our hope. And we're looking forward to discussing that, dissecting that, challenging that in the AI and I care magazine. So look forward to having that conversation with you and with all the contributors in our audience.
And thank you so much for listening. You've been listening to Real Talk, an AI and I care, your weekly podcast to keep you informed about AI technologies revolutionizing I care.