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Artificial intelligence (AI) is rapidly spreading throughout the realm of medtech as companies from every corner of the market look to adapt to the latest in innovation. Whether you’re an industry giant, or a shiny new startup, advancements in AI technologies are forcing companies to embrace and adapt to new developments—all while altering the medtech landscape in the process.
So what’s new with artificial intelligence? How are companies beginning to tap their potential, and when will we begin to actually see the impact they can have on the world of healthcare? These are some of the questions that Gioel Molinari will be addressing at next month’s MD&M East 2018 conference in New York, where he’ll be part of a panel discussion on the topic of “How Artificial Intelligence is Moving the Needle in Medtech.”
Molinari is the current president of Butterfly Network Inc., a cutting-edge technology company that focuses on semiconductor technologies, cloud platforms, and artificial intelligence and deep learning technologies that can shape next-gen devices. Recently the company has been working on a new diagnostic ultrasound technology, known as the Butterfly IQ, that uses a chip technology to transform any smartphone into an ultrasound imaging tool.
Molinari has spent the better part of the last decade monitoring the latest in AI and deep learning developments, with a specific eye on the impact they’ll have on both healthcare and the realm of medical device development. To that end, we decided to sit down with Molinari ahead of his panel discussion to get a better idea on how AI technologies are moving the needle in medtech, and what companies need to do to adapt to the changes and keep up.
MD+DI: For starters, AI technology has long been heralded as the technology of the future in the medtech world. Do you think we’re finally on the verge of tapping into some of that potential in transformative ways? How soon do you think AI technologies could begin to change the healthcare landscape?
Molinari: When deep learning entered the mainstream in 2011, it really marked a tipping point: AI had become better than humans at object recognition. That moment seeded the beginning of the deep learning revolution across industries. We have already started to see the impact in healthcare, for example, in the diabetic retinopathy applications developed by Google that perform better than humans. We are starting to see other areas such as workflow automation and genomics being impacted in the latest wave of AI applications in healthcare as well.
MD+DI: What areas of healthcare do you think will begin to feel the effects of AI technologies the most over the next few years? Where do you see the most immediate impact being felt?
Molinari: I see an impact in three segments: consumers, care providers, and the broader healthcare economy, which includes payers. For consumers, we’re seeing AI applications in vital sign monitoring and remote monitoring of cardiac issues among others. For healthcare providers, we are seeing AI augmenting the professional. This man/machine interaction will be used to automate repetitive, low-risk tasks. Professionals will perform the higher order cognitive tasks, such as inference and connecting context and information across medical and non-medical domains to make sense of them as a whole. For payers and the healthcare economy, AI will be used to make sense of population health and healthcare analytics that will drive efficiencies in costs and services.
MD+DI: What are some of the biggest challenges facing doctors and healthcare workers who are trying to integrate new AI technologies into healthcare? How do you think these challenges will be addressed?
Molinari: There are different classes of challenges. The first is creating the sense of trust and value in the technology. We need to show that these technologies do not add more burden to the workflow, as has been historically been the case in medtech. The second is making AI explicable, transparent, and intuitive. It is vital to reduce the black box phenomenon that may exist with AI interpretation so the user can really understand what is happening. We need more transparency so people can gain trust in the technology, and the amount of oversight can be reduced.
MD+DI: On the other side of the equation, what are some of the biggest challenges that patients will face when it comes to adopting new AI technologies? How are companies trying to address this issue?
Molinari: One of the challenges is the same as the one I described for healthcare providers—gaining trust in the technology with transparency, openness, and clarity. The second element will be the challenge of sorting through the signal versus noise from the many messages that will be coming at them from vendors and healthcare providers offering all the different benefits from AI technology.
MD+DI: What impact do you think AI technologies will have on the cost to patients who receive treatment from these new devices? Do you suspect these technologies will be cheaper in the long run?
Molinari: My sense is that the cost impact is going to be neutral in the short term because there’s going to be a bit of experimenting and trial and error to figure out the right applications for AI, and some will be successful while others won’t. In the long term, there is going to be a very substantial impact, particularly in the more-repetitive and data-intensive applications.
MD+DI: What’s a specific AI technology or application that you’ve got your eye on that may be flying under the radar, and what kind of an impact do you think this technology could have?
Molinari: The application of artificial intelligence with the Butterfly IQ is what I am most excited about. I hope your readers will stay tuned for some exciting news!
MD+DI: Finally, in a broad sense, how do you see AI technologies moving the needle in medtech over the next 5 years or so? How do you see companies adapting to some of these changes, and what will that mean for the healthcare industry as these companies evolve?
Molinari: The era we are entering is a perfect opportunity for disruptive innovation. I believe this era will favor the smaller companies that are able to attract and retain the talent needed to this whole new class of problems. This is the kind of environment where startups with innovative ideas are going to flourish, while larger players struggle to develop and integrate these technologies in their entire business quickly.