 What a wonderful pleasure to be with you here. Thank you, Dr. Ramsey, Dr. Masumi, Professor Najim Mashkati. Thank you all for having me here and giving me the opportunity to talk about some issues that are of pressing importance. And what I would like to do is give us hope about implementation today with technology that's already available. I'd like to have some disclosures of the NIH and the Human Research Program at NASA that have funded some of this work. But at the heart of the matter is this. So who am I? I was born in Mexico City. And I'm essentially an engineer and a new scientist and inventor with a passion for combining engineering and biology. And so what we do in my lab is we create a community of individuals from a variety of backgrounds. And we want to solve problems at the interface of engineering, AI, physical therapy, robotics, biology, neuroscience, medicine. So it sounds familiar, right? It's understanding how the brain works and how it controls the body and needs a multidisciplinary team just like the healthcare system. And so what I'd like to do today is confront you with a very, very scary number, the number 17. And you wonder, well, what's the number 17? Well, it actually takes 17 years for those of us who are producing solutions and doing basic science and coming up with cures and coming up with new methods in medicine. It takes 17 years for 14% of those solutions to actually reach clinical practice. And if this sounds incredibly long, it is. However, the question that we have now is can we actually use technology to reduce that time? Can we use technology to reduce harm and deaths? Can we use technology to reach zero unnecessary deaths by 2030? And I think in some domains, it would be possible. And being an engineering professor, you will excuse me for maybe bringing up all these fancy terms, but Professor Mishkatty is an expert in this. The question that we're facing is very well known in engineering systems. It's knowledge to action translation. How do you take knowledge and make it implementable? And it's a very well known problem in many human systems, in many engineering systems. And what's interesting about this is that there's a whole theory about how to do this, but the only three things you need to know are how is it that knowledge gets put into practice? There's the usual way, which is diffusion, where you just put up a website and you have passive, untargeted, unplanned spread of information. Here are best practices. Please come to our website, read them, use them. Then there's dissemination, which is active marketing of these ideas. This is the planned and directed spread of information to your target audience. And then this is where the rubber meets the road. You have implementation. How do you actually take that knowledge and translate it into action in the setting of interest? And of course, what are the impediments to this? Because this is why we're here. How, we already know the solutions. How do we actually implement them? And actually, most of the impediments are social. In particular, if you have a high risk treatment, if you have an implantable device, you want to move very cautiously like the FDA requires us to do with class three devices. Many options, you want to find the best one that does the most good and no harm. Get a best practice. The other problem that we have is we often think of the developments in science that are being developed for the good of patients. But then we consider patients and caregivers and the medical system as essentially passive recipients of our knowledge. And of course, from what you've heard here, that doesn't work. We have to work in a team in collaboration with our patients. And in terms of implementation, once you've done the heavy lift and you actually have the solutions, how do you implement them? There will be skepticism. There will be cost. There will be time necessary. You need training. You need technology. So this is how usually the medical system works. But what I'm here to tell you is that we actually are working in a very interesting space where this does not apply at all to low risk methods and devices and even consumer products that bring immediate benefits today. So we do not need to be beholden to that long 17 year gap, right? So in fact, the problems and the solutions are known. They're so well known that we actually have the actionable evidence-based practices. And what's so interesting about these evidence-based practices is that if you go to the website of the Patient Safety Movement Foundation, they're meant to be used and implemented today anywhere on earth. No development necessary. So what is the main holdup here? Well, the main holdup is the collaboration among stakeholders is the key to implementation. Nothing else. And we've heard some very exciting movements at the level of policy, at the level of governments, at the level of systems of hospitals, individual hospitals, about how we could do these institutional changes. However, in my own experience developing medical devices, for example, we have technology that are essentially low risk. They're cloud computing enabled. They're internet enabled. They could help patients today for rehabilitation, for knee replacements, knee injuries, chemotherapy, induced neuropathies. And interestingly, we're working with NASA because we see these as a way to promote health in astronauts on their way to Mars and while living on Mars. So it would be the height of irony that these types of technologies that are easily available get implemented on Mars before they're implemented in the oncology clinic next door. I mean, I hope you agree that. Maybe we could actually go next door. So what I'd like to say is just remind you what the internet is. The internet is an infrastructure for information that allows people to communicate. I send you an email, you send me a text, everything is fine. But in parallel with this, what we've seen is that there's the emergence of another internet, which is the internet of things. My toaster talks to my refrigerator. My smart speaker talks to my television. My television talks to my vacuum cleaner. Information is being transferred. And that's very good. However, this can also be leveraged in some ways to help practitioners, patients, and caregivers connect with each other. Let me explain how. And before I do that, I have to introduce you to another very popular term that is so ubiquitous. You may not know it by name, but you've been doing it all morning. It's called human in the loop architecture. When you get a reminder in your calendar, hey, your talk's at one, that's human in the loop architecture. When you are watching your favorite movie on a streaming service and it asks you, did you like this? That's human in the loop architecture. So there is a body of knowledge, this information, there are devices. But the human is a critical element that is asked very few, but very critical questions. Was this movie good? Did you like this recipe? If you do, may I suggest this other one? That's happening all the time. It's happening so often that you don't even recognize that that's happening. And of course, this is also happening in the medical domain. In the medical domain, you could have a radiologist that is checking those few and far between x-rays that are not easily readable. You need an expert human. In the loop. Okay, so given that that's what's happening, then you have the internet of medical things. You could have blood pressure monitors, heart rate monitors, any medical device that is manufactured by any of the many companies in the space is essentially, potentially, an internet of medical things member. So what I'd like to do is, and this is my main message here, we can take the human in the loop architecture and make it into a people in the loop architecture, where instead of having one human that's doing the annotation or looking at a particular problematic picture or x-ray, whatnot, what you can do is you could have clinicians, one, two, or multiple clinicians, locally at that hospital or anywhere in the world that are seeing this stream of data where the AI, whatever that may be, it could be as simple as a table, that says, hey, we noticed this. And then the clinician does something or gives an opinion, but importantly, the family, the caregivers, the patient, they could also be in the loop. Like how many times are you not joined into the group that are telling you how nicely their vacation is going and here's a picture of my cat and a movie of my dog? Well, that information is being shared among people, everyone's in the loop, so then it is very possible to use these existing architectures to address these problems. And in particular, just to ground these ideas and tell you a little bit about what's happening, we could talk about, for example, pressure ulcers. Did anyone get a message from your smartphone or your smartwatch time to stand up? Well, if you stay sitting, you will get a pressure ulcer, right? So why don't we actually do this in hospitals, in hospital beds? Or hand-off communication, when you're organizing a dinner party, they tell, oh, actually, the restaurant changed. We're not gonna go somewhere else. Well, when a new shift of clinicians comes in, they actually get a little text that says, hey, watch out for this particular situation. This is the particular problematic issue with this patient, right then and there. Also, if you have a situation where you like to, you're driving your car and it tells you, turn left, turn right, go straight, you could also have a situation where it says, high temperature, interesting. No hunger, the person might be actually going into sepsis. So consider sepsis, just from the very simple information that's being transmitted. And for this, you don't need big data, little data suffices, just a few data points. You don't need deep learning, you just need shallow learning. It's like, oh my God, the person hasn't eaten in two days. And this is a way in which you could just remind people in a very flat hierarchy to say, hey, consider sepsis. It's an option and nobody's ego will be hurt, right? If you get recommended a movie or a recipe by your telephone, your ego is like, oh, okay, well, maybe I'll try it. There's no problem there. So this is a way to democratize and flatten the strategy. So in summary, what I'd like to just say is we can improve patient safety individually or as a system as a process today. While we're making all of these changes to the structure of the institution, the legal structure, the medical framework of how to save lives, we can nevertheless already apply those best practices. How? By using currently available technology to invite patients, caregivers, families into a collaborative network that is informed and sustained by the information and the infrastructure that we have, right? And then just simple messaging among participants. You already do that. We can also improve real-time reminding and reporting and detecting of events that are relevant without the need for big data. Sure, that will come, but in the meantime, we could save lives. Also, and very importantly, we're actually distributing not only responsibility, but we're also distributing the benefits of such a collaborative environment. And these are usually low-cost wearables, sensors, edge computing algorithms, databases that are already available today. So what I'd like to do is I'd like to invite you to consider these, you could say they're complicated words, right? Internet of medical things combined with people in the loop architecture, which are actually used in many industries already. I'm not the first to propose these kinds of things, but they could reduce unnecessary deaths by accelerating the implementation part of the equation, which is a rubber meets the road. It can also help enable patients and caregivers and have them be actual participants and collaborators in this effort, not passive recipients of care, passive recipients of information. And also mitigate the skepticism and promote collaborations by having a very flat architecture. I don't get upset when my watch reminds me that my meeting is about to conclude that I should stop talking. It's like, okay, well, that's just how things are. And then this way we can transform patient safety with the people in the loop architecture. And thereby apply these best practices today. And I think I'm very hopeful to be able to reach zero unnecessary deaths by 2030. Thank you so much for your attention.