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- [00:01]
Roland Roth
We were very focused on using AI to create solutions which make an impact on patients.
- [00:10]
David Meyer
That was Roland Rot, CEO of GE Healthcare Imaging segment within GE Healthcare. Our David Meyer and Asit Sharma talked with him about everything from GE Healthcare overall to a bunch of examples of how AI is used in healthcare to both enhance efficiency and to boost patient outcomes.
- [00:34]
Hello, everyone, and welcome to this installment of the CEO Interview. I'm your host, David Meyer with my foolish colleague, Asit Sharma. Asit, how are you doing?
- [00:44]
Asit Sharma
Very well, David. Excited for this.
- [00:46]
David Meyer
Yeah, me too, because we have an incredible guest. We have the CEO of GE Healthcare Imaging, which is a $9 billion segment within GE Healthcare, Roland Roth. Hello, Roland, how are.
- [01:01]
Roland Roth
Hello. Hi, David. Hi, Asit. Hi, everyone. Thanks for having me. Looking forward to this conversation.
- [01:08]
David Meyer
We are too, and we're very glad to have you. So let's kick off and start a little bit broad and talk about GE Healthcare, the overall business, sort of what its business model is and what its mission is.
- [01:28]
Roland Roth
Yeah, David. So GE Healthcare, I'm sure many of you will know, has been part of General Electric for the first 123 years, if you will. Right. So General Electric was a very iconic American company, highly successful in many fields, Healthcare being one of them. So we have been essentially over 100 years in healthcare and have been at the forefront of innovation and all these generations of medical devices and medical imaging. Now, what is very exciting is that a couple of years ago, beginning of 2023, we actually spun out of General Electric and we became an independent public company, so traded at NASDAQ, now being an independent, freestanding public company with approximately 19, $19.6 billion of revenues and serving ultimately more than, you know, a billion patients worldwide. 1 billion patients worldwide across 160 countries. So it's a very significant impact. This company has a very strong legacy, but very exciting future ahead. Also in this new phase of being a public company ourselves.
- [02:42]
David Meyer
Yes. So a long time ago, I used to work at GE in what was known as the power systems segment. And I have to say, GE Healthcare, back between 1998 and 2005, was always held up within the company as a great model. And so maybe let's talk a little bit about its business model. And that is how do hardware sales, software sales, service agreement, how do those all tie together to basically be the operating engine for GE Healthcare?
- [03:14]
Roland Roth
Yeah, great question. And if you think about medical imaging and healthcare overall, what we provide essentially solutions in order to detect diseases early, to diagnose disease, to ultimately support treatments and monitor these treatments, monitor the health of patients. So as GE Healthcare, we are active in all this spectrum and we are doing that with a strategy which is what we call the D Free strategy. So we want to provide smart devices, devices which are smart, which are intelligent. We will talk about artificial intelligence. So they are substantially AI enabled, but also smart drugs. And we align those smart devices and drugs on certain disease states, for example cancer or cardiovascular disease. And then we also provide digital solutions. We leverage the data which these devices are generating in these specific disease areas as physicians use it, and putting all that together provides solutions which can really improve and impact patient outcomes. So that is in essence what we provide. Again, relevant hardware, smart devices. Think about systems like CT or Mr. Ultrasound devices. So these are technologies which allow physicians to take a look at patients conditions and then using the relevant software to get to a good diagnosis and to ultimately make meaning of what these devices actually are producing. And from a business model standpoint, once we are offering this devices, they are obviously in use for an extended period of time. So we also provide, you know, services in order to keep everything not only up and running, but also up to date. So we also keep customers vital with newer possibilities such as new versions of AI, etc.
- [05:05]
Asit Sharma
Roland, let's stick with product for a moment. Could you break down for our members what are the major product areas within the imaging segment?
- [05:16]
Roland Roth
Yes, so I would define, you can almost define it by the generation it was sort of created. So when imaging was starting like 100 years ago, we only had X ray, right? X ray was the first modality and it was a foundational one for many further on, technologies like mammography is a piece of it, which we use in breast cancer screening. We then had the rise of ct, which is again technology wise, X ray based. Then came mri.
- [05:46]
Asit Sharma
Right.
- [05:46]
Roland Roth
A very revolutionary way to look inside the human body without ionization and with very powerful capabilities. And I would say in the last phase you have this field of molecular imaging which essentially combines some of the traditional capability like CT and Mr. With additional sensors, with additional detectors which can actually allow physicians to look at inside or they find cancers through radioisotopes. So radioactive drugs, slight radioactive drugs which are injected and ultimately can visualize and target specific cancers as an example. So very, very advanced technologies from a standpoint of imaging. And as you see in this range, all of these modalities have their particular areas of use, they have their designation, they have obviously their different reach. It's easier to deploy a mobile X X ray device than a big iron, if you will. Mr. Device or a PET CT system, but they have a significant impact on patients.
- [06:59]
N/A
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- [07:28]
Asit Sharma
And if I were to ask you out of these, which products maybe are driving most value for the imaging segment, what would those be? I have an idea that part of it might be related to the PET type products. So these nuclear tracing products. But would love to hear from you what is looking into the future, the biggest driver of value for going forward?
- [07:51]
Roland Roth
Yeah. So if we look at it, we can look at it from a lens of patients and obviously from a lens of, you know, from, from a financial and from a business standpoint I would really starting on the patient side, we always put patients first. We would say that, you know, there's, there's, at least in mature markets there's good coverage on some of these earlier imaging technologies, but there is yet a lot of potential to, to provide patients more access to cont. Temporary MRI or to PET CT and PET. Mr. So this molecular imaging space, these are areas which keep growing substantially because a, they don't have the visibility. And on the other hand molecular imaging or theranostics which combines therapy and diagnostic actually is still growing in its clinical applications. So there are more types of disease which can actually be handled with those technologies. So we do expect from a business standpoint significant growth over the next years in these areas of molecular imaging, advanced therapies, but still also in these traditional technologies you could say, which help reach more patient or make decisions more efficient in order to handle the patient volume, which we simply have to deal with.
- [09:07]
Asit Sharma
And from an investment standpoint, I'm curious, where are you focusing most of your R and D look?
- [09:15]
Roland Roth
I think in general when it comes to R and D, we work in the lifecycle approach vis a vis all of these technologies. So we have opportunities for example in CT to work on some more advanced next generation capabilities. As we announced, we're working on a deep silicon, a silicon based photon counting architecture which, which we believe will take the possibility of CT another step forward. Right. And that after CT has been around for such a long time, when we think about molecular imaging, it's a big area of investment because there is so much new capability with new radioisotopes available. So in that sense it makes sense to invest further in creating more applications and putting these technologies in the hand of more physicians. So ultimately we do invest today as we are a standalone public company, factually more than ever before from a nominal standpoint. And we have a rich pipeline which definitely fuels further growth based on that investment.
- [10:32]
David Meyer
Yeah, I think this is a good segue to talk a little bit more broadly about innovation, especially since you're at all time highs for R and D budgets. Innovation is definitely within the lifeblood of ge. When I was there it was extremely important and became even more important under Jeff Immelt when he became ce. And that's when I left. But I'm sure it's still extremely important to the culture. Maybe. Can you give some examples of how innovation is working within healthcare or imaging if you wanted to go specifically there? It can be anything. It can be maybe a product upgrade or even, you know, a major breakthrough that gets you into a new market.
- [11:18]
Roland Roth
Right. Look, I would say one of the biggest areas of innovation and also going back to investments is, is of course artificial intelligence. AI. Deep learning. Right. In the context of health care, AI has been around for some time, right. So AI principle has been around for several decades. However, with the, with the rise of, you know, possibilities, with the, with the possibilities. Nvidia provided us, for example, to have very powerful capabilities within a computer. We are now able to process large amounts of data and that ultimately can help to make these systems and smart devices even smarter. So we invested significantly in AI today. Actually we are a leading company in the field of AI. We have more than 85 cleared FDA cleared medical devices today in the market. So they are clear they are commercially available and they help physicians to treat patients more efficiently and on the other hand, deal with this large amount of patient volume and get to better insights. It's really important for us to help physicians and see AI as a partner. Often it's used as a co pilot to augment the possibilities of physicians and helping them get to the result with confidence as efficient as possible. And that will also help to improve the outcomes. So if I give you a few examples, we have been able with AI to streamline the reconstruction time first of all, and the processing time in Mr. By more than 70% and in cardiology even 83%. So we are able to slash these exam times and that means it's more comfortable for a patient. You don't need to lay in such a device for an extended period of time, think about many patients which are in the queue. If you can be faster, you can handle more patients in the same time frame. And ultimately we have also been able to improve that image quality. So make this image quality more robust, take certain artifacts away, et cetera. So give the physicians a cleaner image in that sense, ability to confidently screen a diagnose. So this is just one example where AI already makes a significant impact. And with the technology I described, we have already handled more than 30 million patients actually. So this is quite proven. This is not in the infancy stage.
- [13:54]
David Meyer
Maybe I'll follow on with an AI question and we'll start internally and work our way out. So it's very clear that data is, the creation of data from your machines is very important. Maybe internally, how are your teams using AI to maybe get a little bit more marginal in return on the R and D budget, things like that.
- [14:23]
Roland Roth
So I would say it's very interesting, your equation, because we can use of course, AI for creating solutions. We can also use AI in the process of creating these solutions. My early example, and that's really our evolution, we started with customers first, we started actually to use AI first, you know, to create solutions which make an impact. And maybe it also related to the timing because we were in Covid, we had a lot of, you know, challenges in many of our customers and physicians had challenges to deal with the load of patients, etc. So we were very focused on using AI to create solutions which make an impact on patients. And while doing though right, we, we then in recent years spent also quite some efforts to look at the process. And as you will know, there's a lot of documentation required in medical device generation. There's a strong quality management framework which we are adhering to regulatory requirements. So today we actually find a lot of opportunity to use AI to augment our engineers in doing exactly that work and also be more productive that way, get more agile, shorten some of the creation time or if you will get more output in the same period of time. That last piece still has a lot of potential. We are just at the beginning really of unlocking that. And I think we're going to keep learning and we're going to keep evolving obviously, as we also get more possibilities with AI.
- [15:58]
David Meyer
Maybe before ASIT asks his question, I'll just have one comment. So I used to be a black belt in the old Six Sigma realm. Is AI basically Six Sigma on steroids now? I mean, it's like the next 10 levels higher type of a thing.
- [16:15]
Roland Roth
Yeah. So maybe to translate. So Six Sigma is one approach which also General Electric has used early on and also relates to lean. Right. And Lean is very much a culture, and it's also a. A set of tools of continuous improvement and to take waste out, for example, of processes. So in that sense, you could say AI is a close cousin. It's a tool which allows us to do exactly that. And ironically, as you mentioned this point, we actually implemented Lean or reimplemented Lean very substantially over the last years in parallel to AI. We deployed lean very. Consequently, Larry Kalpu is the CEO of GE and came into ge, is our chairman today. This vast lean expense inspired that. And today actually we both deploy lean and use AI to get more, to get processes more efficient, to take waste out, to actually speed up and be productive, all in the spirit of serving customers faster, but also obviously as precise as needed.
- [17:19]
N/A
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- [17:48]
Asit Sharma
I want to go back to something that you mentioned earlier, because I think many of our members will have an interest in sort of the competitive edge that Imaging Solutions has. You talked about the clarity of images that have been enabled by AI. So basically we have a scan, and in any number of outputs, you have a visualization, which is then, I would call it as a layperson, almost recreated by AI. So some of the noise gets removed and you have more signal, the image has more clarity, but at the end of the day, it's an algorithmic type of improvement. So we're sort of curious, what kind of edge is this vis a vis competitors? For example, someone using these images, a physician maybe, has a higher confidence level in his or her diagnostic capability. If the image is better, and as you already mentioned, it cuts down on the time it takes to run the test and get all the way to a diagnosis. Is this something that a competitor could also working in an AI kitchen, come up with? Or do you have some type of clear edge versus those who offer similar products?
- [18:59]
Roland Roth
Look, I think, in principle, and that's always true, all these capabilities are, in theory, available to Many. Right. And so we see a lot of innovation, generally speaking, when it comes to AI in healthcare. And let me also say that we are cultivating a pretty open ecosystem. So we are not only creating our own AI, we are partnering very closely with customers which can be very large healthcare systems, generating a lot of data, applying that, having their own models. And then ultimately that can lead to some startup which ultimately offers that and we integrate that. So we are really using, you know, the broader ecosystem lands here. We have also acquired a few companies over the last years in the space of AI, such as Caption Health in ultrasound or mim. Right. In the, in the space of molecular imaging software, as I mentioned before. So they all use AI and they all are augmented enhancing, so to say what we organically do. But really to your question of competitiveness, we do believe, and based on the facts that we started earlier, we have a lead in, you know, FDA cleared medical devices today. A lot of customers look at that and understand that, yeah, we created, we invested into this space. We created meaningful, impactful solutions. And that gives us credibility to further charge ahead in creating, you know, further such solutions. We have just, we have just started, if you will, with these first 85. But some of those AI applications have been very narrowly focused on improving a certain image area and so forth. But we have now extended the field quite broadly to also create solutions which combine such exams across modalities. So think about a care pathway where a patient first gets diagnosed with an ultrasound system or gets screened with an ultrasound system. In mammography, you use mammography, you then use MRIs. So you go through these different technologies and as more and more data is generated, how can we use AI also to give physicians a comprehensive summary and comprehensive insight about the patient's condition? Those kind of applications are actually now really interesting based on the possibilities we have found. So it's really innovating that specific individual smart devices as one, but it's creating solutions across the care pathway which have a lot of even more impact.
- [21:45]
David Meyer
As always, people on the program may have interest in the stocks they talk about. And the Motley fool may have formal recommendations for or against. Don't buy or sell stocks based solely on what you hear. While personal finance content follows Motley Fool Edge editorial standards is not approved by advertisers. Advertisements are sponsored content and provided for informational purposes only. See our full advertising disclosure. Please check out our show notes. That's all for today. We'll see you tomorrow.