Okay, so good morning. I'm Dustin Haines, the CEO for Echo IQ. We are a company traded on the Australian Stock Exchange and just recently listed on the OTC, as we're shifting our business into the U.S. Echo IQ, what we are is a health tech company that is looking for diagnosing patients earlier and more accurately for heart disease. Specifically, I'll talk about aortic stenosis today as well as heart failure. Before I get started, though, I do have to tell a story. I don't know how many of you ever kind of listen to the cosmos or believe in fate or stars aligning, but every now and then the universe talks to you. This happened to me a few months ago, and sometimes you just have to listen. I was at a family reunion.
I bumped into an aunt, hadn't seen her for 15 years. And so she told me her story. And her story was that about three or four years ago, she started feeling sick. She had lower back pain. She was fatigued. She was tired. Every now and then she'd get some chest pain. And this is a late '60s, early '70s-year-old woman who is in great shape. She's a yoga instructor, rides bikes, hikes. And she was frustrated, bounced around the health system, had an echo done with a cardiologist, nothing was found. And ultimately, about six, seven months ago, she fell off her bike and broke her leg. Went to the emergency room. The internist at the emergency room decided to do an echo, and lo and behold, she had severe aortic stenosis that she'd had for quite some time.
And I tell that story only because I think it's a significant story that talks about something that happens far too often around the United States, and it actually happens quite often around the world. And it's not necessarily always the fact that it's women that are disproportionately or misrepresented for diagnosis and underdiagnosis of aortic stenosis, but unfortunately, it happens quite significantly. And so what we're here today is to talk about a little bit around is how do we help solve that problem, not just for women, but for all patients who show up getting an echocardiogram. Because at the end of the day, we want to make sure every patient has the ability and the benefit of getting accurately diagnosed every single time.
And so hopefully, there's nobody in this room that has a family member, a loved one, or a friend that has to go through the same thing. And I think technology is now getting to the point where we can start to make sure that does not happen. So what do we do at Echo IQ? That's a question I get all the time. And so I'm not a really intelligent individual, so I have to dumb it down to where I can understand and explain it. And if you'd forget anything out of the whole presentation, the one thing I'll have you remember is that at Echo IQ, what we do is we help physicians to diagnose more accurately and more quickly structural heart disease. That's as simple as it is. I don't replace a cardiologist. I don't create some fancy hardware that's sitting in the clinic.
I simply help them do what's a very complex task, and I make it a little bit easier for them. And we get it right nearly every single time, which is the most important part. Now, this is incredibly complex, and obviously, it's quite technological. But at the end of the day, we serve a very simple purpose, which is to make sure we're getting these folks diagnosed accurately. So we work directly at the point of echocardiograms. So if you haven't had one or you don't know exactly what an echocardiogram is, it's quite simple. It's a 2D, basically, ultrasound. So it's the same thing that a woman would get if she's pregnant and wants to know the sex of the baby and the health. This is what you'll get. An echocardiogram, is quite rudimentary in its technique.
It's not super high definition, but at the end of the day, it's a very effective tool to help get that initial diagnosis for patients. So we've actually created an AI model. It's a multidimensional neural network that actually takes a unique proposition we have here that is different than everything in the market. And we actually start looking at the measurements from the echocardiogram, not the image itself. So if you run into other companies, you see it on CT, you see it on MR, and you see other companies looking at echoes, what you're going to see is image recognition. Absolutely fantastic. Those are great tools. Biggest problem, if you have a bad image, poor image, or no image, guess what? The technology doesn't work. So the way we've developed our algorithm is simply looking at the richness of the data that comes from an echocardiogram.
If you look at the images there, you'll see all those orange dots there. Those aren't actually on the echocardiogram. But what our technology does is it takes every one of those dots that represents a measurement, a metric, or a number, and we strip the images out, and we simply use the data behind those images. What we actually do is we create what you see here on the left side of the screen, which is a 3D version of that patient's heart. In fact, what it is, it's a phenotype of that heart. We call it a unique risk fingerprint. That patient now has actually got a phenotype in the neural network. The neural network now can compare it to over 1 million echocardiograms it's trained on, and it delivers two things back to the cardiologist in real time, instantaneously.
The first thing it does is it presents back presence of a disease. So in this case, we're talking about aortic stenosis. The physician will get a very clear output that says the patient has presence of guidelines-defined aortic stenosis. The second thing, which is unique to us and unique to what we do, is that we will provide them a phenotypic risk score. So for the first time, as a cardiologist, is trying to understand what's happening to the patient, they're trying to create that phenotypic risk in their mind. We actually give it to them on the spot. We can actually show them severe, we can show them moderate, and we can show them mild, so basically traffic light system. And in that moment, the cardiologist now, for the first time, can see what they can't see in the echo.
And we can actually show them on those severe patients, those moderate patients, where those patients fit on a risk stratification. And the bucket that we find, that's that severe risk stratified patient, mostly women. Mostly women because they present differently in the clinic. They're going to present with fibrosis around the valve and probably not calcification, harder to see on echo. They're going to have low flow, low gradient. They're going to be harder to see on an echo. We find those patients, and we bubble them up to the top for the physician. So the unique benefit of that is we work in real time. We work right where the physician is working in their workflow, and we provide them very accurate diagnosis of presence of a disease and a phenotypic risk score. Our area und=er the curve on this is 0.986.
So if you're thinking about those numbers and that perspective, we're dang near perfect on being able to diagnose aortic stenosis. And I've got a couple of slides that I'll show you on the clinical data that we're very, very, very happy with. So what does that really mean? Well, we feel like we are very poised right now for a unique opportunity. When you look at strategic pillars of success for commercialization, we know we've got real-world evidence. In fact, now the model has been run over 2 million echocardiograms. We know that we can produce data that's replicatable in the real-world setting. We don't believe in the fact that you should do one validation study, throw an AI model out in the wild, and hope. That's not a strategy. We should be delivering clinical evidence plans to do that. We've got real-world evidence.
The second, if you stepped into a hospital one time, you know one thing very clear. Workflow, is the most important thing that happens at a hospital. We are seamlessly integrating into existing workflows as we speak. So when we integrate, we integrate directly in the PACS system, so that the cardiologist, is looking at the same monitor that they're looking at for their echocardiograms. I don't change the workflow. I make the workflow better. My integration is simple because we are a SaaS product sitting in a cloud-based format, meaning we can connect to any hospital regardless of whatever machines they have, whatever technologies they have, simple, easy integration for their technology. And we work in real time. And the final piece is you've got to get paid.
There's a reimbursement pathway here for the folks in the room that have worked or been part of the HeartFlow, the recent IPO coming out. You know reimbursement matters. CT space, right now is doing incredibly well for reimbursement, and we're seeing the upstream effects of that in echocardiograms now, where you can start to see category CPT codes available. So we believe we've got a strong path for reimbursement and a strong revenue path going forward. It only matters if there's a big market, and I don't think I would surprise you guys to tell you how big the markets are if you look at aortic stenosis or you look at heart failure. These markets are large, and they're growing. They're growing, obviously, because we've got aging population, but they're also growing because in America, we tend to have a lot of unhealthy people.
Whether that's the new Type 3 diabetes of obesity or whether that's the fact that you've got hypertension or you've got diabetes itself, all of these play a factor in the growth that you're seeing in these markets. We believe that we're going to have a major impact on changing the calculus of these markets. When we think about the data, this is what I'm most happy about, what we're doing. We have to be able to replicate and have clinical evidence behind the AI technologies. It can't just be a one-and-done. They have to be able to continue to show that in the real world, you have clinical evidence. This is four studies that we've either recently just presented or published in major journals.
I don't need to read all the slides on here, but what it shows you is that we have brought this technology across multiple different centers, across multiple different geographies. You've got international data. You've got Australia data. You've got the U.S. data. And the thing that's the most important here, large data sets, you can see that we typically reach 100% effectiveness in diagnosing severe aortic stenosis across these data sets. So that tells you not only do we get the validation, we have the FDA clearance for the technology, but we continue to show real-world evidence of the technology working very well. And at the end of the day, that's somebody's mother, that's somebody's grandfather that's getting the accurate treatment and the diagnosis that they need. So today, for aortic stenosis, FDA-cleared product in the market. We launched it in the first quarter of this year.
We're integrating through a number of different hospitals and systems as we speak. But we're very excited about what the future has to hold for us. So I'm going to show you a couple of slides that we don't have yet done, but we are working on a heart failure solution that'll be going in with the FDA within the next couple of weeks. So I'm going to show you two clinical slides. So our first one was the validation data on the heart failure. This is obviously a huge data set. So you can see the number up there. It's 631,000 individuals broken out by training set and test set here. And we were looking for, could we affect change in heart failure? And right now, the clinical practice experience is around 46% accuracy in diagnosing heart failure.
This is a very complex disease, and it's not easy to do. When the AI was running, you can look at the middle bar there. The AI by itself got to 86%. Phenomenal results. We almost doubled the number of patients that were missed from the diagnosis. But we put a third arm in because this is an important element. How much of the physician's experience can actually help drive the overall utility? You can see in this study, we got 97%, increase by just bringing the cardiologist expertise in, which means I'm not replacing a cardiologist. I'm just making them better at what they do. This was the hypothesis for us to go into our clinical validation and talk to the FDA. We had a really good pre-sub meeting with the FDA. We agreed on a protocol, and we agreed on a partner.
So we had a great partner with the Mayo Clinic, who did our validation study. Timing is amazing because it just came out last week. So you guys are seeing top-line results that just came out last week. I don't know if I have to say a lot about the slide, but our sensitivity and specificity analysis were beyond expectations of the company. So as we continue to show the technology being working in different data sets, you can see now we're at 99.5%, sensitivity and 91%, specificity. Nobody in the market has any sensitivity and specificity over 90%, that can match the technology and the benefits that we have there. So this is going to lead us, obviously, now to an FDA submission that we'll be doing this week.
Hopefully, if not, it'll be next week into the FDA by end of this year for clearance sometime in early 2026. So this will put our second solution in the market, working on the same platform. So we're very excited about what we have in store for us for 2026 with the organization. And now the question really is, what does the longer future look for us? Obviously, we're not a single-point solution. We believe in bringing a platform to the market. I have a very unique, what I would call a competitive moat in this space. I've got a partnership agreement with the National Echo Database of Australia. This is the largest database in the world that has longitudinal patient outcomes. So when I look at my data, I actually can compare it to mortality.
I know what's happening to my patients because we can do retrospective analysis, look forward to see what's happened. So everything we do now going forward allows us to build off that platform. So you're going to see work from us on hypertrophic cardiomyopathy, pulmonary hypertension, mitral valve regurgitation, and about two or three others that we're continuing to explore as we speak. The goal here is that we can continue to build the business and build a platform, an end-to-end platform for a cardiologist in the echocardiographic space. So our commercial pathway is very clear. We've got three clear strategic pillars. We're working on those now when we're delivering that in through revenue growth in 2026. We've got hospitalizations, hospital integrations, the most critical part of our success factor here.
We're integrating a number of hospitals now in the U.S., including our flagship site, which is Beth Israel Deaconess Medical Center, up at the Harvard Medical School in Boston, and we're working on a number of large institutions, individual hospitals, as well as some small systems across the country. I believe in democratizing this for everybody. Whether you're sitting in a small rural hospital in the middle of the country or you're sitting in New York City, you should still have access to this type of technology, and we want to make sure it's available for everybody. The second part of our pillar is reimbursement and revenue. We're going to see a significant revenue acceleration in 2026 as our heart failure model comes into the market. We have current CPT codes available for us now, paying at around $250-$300.
Our aortic stenosis model, is reimbursed right now around $150, and we're working with CMS to see if we can get that to a specific code itself. We've got a very short sales cycle in here where we can integrate quickly, a free trial, and then immediately into a subscription model. And then our third pillar is the pipeline platform. We've de-risked that a bit by bringing the heart failure model this far along with the validation study, and we're anticipating having the rest of these come out over the coming years, which allows us to provide that platform play we believe in. So our business is quite clear. We're a scalable business. We know we can scale. We know we have the opportunity to do that, and we've got the team that's building a scalable business.
I wouldn't be a good CEO if I didn't sit here and say the left side of the screen is an important part of what we're doing. We know there's licensing opportunities, whether you're talking to pharmaceutical companies around the heart failure product itself, whether you're talking to device manufacturers, whether you're talking about the valves themselves, or you're talking to any of the hardware and service providers, which we're actively having engagements with all three. So it gives us a chance to both be excited about scaling the business and driving value, but at the same time, having those strategic partner discussions. So with that, I'm going to stop there and see if there are any questions from the audience. Nope. I'm sorry? Right now, we just did a small raise. We raised $17.5 million.
I've got $15 million in the bank, burning about $600,000 a month. So right now, my runway looks good to revenue, but one of the things we'll be looking at is a U.S. IPO potentially as we move the U.S. Inc, into the markets. Yes.
Do we have cardiologists?
Yeah, it's actually a push-pull strategy. Cardiologists are our first point of call, and these are typically imaging cardiologists. But then we've got the administration of the hospital as obviously a big point of call because we believe we've got both a health economic story for them as well as a revenue acceleration story for them. But the cardiologists, first point of call, for sure. And I will tell you, it doesn't take too many calls with the cardiologist to see the value that it brings to their clinic. Okay. Cool.
I appreciate you guys' time, and I thank you so much. Obviously, we're happy to have any other questions afterwards. We'll definitely.