At the heart of an industrial revolution is an innovation that changes everything. Building AI Boston sees artificial intelligence as a renaissance. From the heart of innovation and the mecha of tech learning, we bring you AI for real people, a conversation for everyone. Dr. Ami Bott is the Chief Innovation Officer at the American College of Cardiology. She's a national leader in creating the AI-enabled clinician. In her 20 years of experience, she spent over a decade in telemedicine and digital health. She served as an associate professor at the Harvard Medical School and the Director of Outpatient Cardiology, Telecardiology, and Adult Congenital Heart Disease at the Massachusetts General Hospital, where she designed the MGH Elevate Leadership Program, focused on developing the next generation of impactful leaders in medicine. Today, we get to the heart of why AI can help doctors be more human. Dr. Bott, thank you for being here and welcome to Building AI Boston. Thank you so much for having me. We're excited because you're a great Boston connection, and I know that you did your undergrad, you graduated from Harvard, obtained your doctoral degree from Yale, and trained at Massachusetts General Hospital, Children's Hospital of Boston, and Brigham and Women's Hospital. So you're an incredible representation of what we feel is a Boston state of mind. I know you're not from here, but I want to go back and ask you, what was your inspiration for going to medical school, and how is the psychosystem affected what you do now? Yeah, I like to start with a disclaimer first. You're right, I'm not from here. I was born in New York, raised in Jersey. I was a Yankees fan until Derek Jeter retired, to be honest. But I moved up here in 2001 for residency, for academic training in medicine and pediatrics, and this environment has always been phenomenal for training in medicine. And then I went into cardiology. By no you and I were talking earlier, and in my very first office, I actually had, many people may recognize this. I had a little picture by Norman Rockwell, and it was the one where the doctor's preparing a vaccine, and the child is kind of facing the wall and not looking at it at the time. And that's because that's the part of medicine that I really love. It was the part where each day you get to meet all these new people who within minutes are willing to welcome you into their lives. And then you have to take not only the science, but the science and the person, and put it all together to care for someone. I'm the first doctor in the family, everyone else, or business people. And so it was really something that just spoke to me as a person. It's one of the reasons I'm kind of excited about AI, because the way I'm looking at it today is a way to get us back to that. We've gotten a little far away from it, and to be able to bring us back to just spending our time, person to person in a personalized way, understanding what people need, and then delivering that. I will say, speaking of Yankees, my daughters were born in 2007 and 2013, so we are now absolutely red socks family since those were both series years. So, you know, I've come a long way. You have come a long way, and I want to just give a shout out. My father-in-law was a physician and had the same Norman Rockwell painting, and I love that you're bringing in the human element, including the shout outs to your family. That's beautiful. Thank you for talking about the human element of this conversation right off the bat. I appreciate it. Absolutely. Yeah, and there's this wonderful museum up in New Hampshire and Tamworth, New Hampshire called the Remick Farm Museum. And it's one of my favorite places to go, and it's a farm, a working farm, but it also has Dr. Remick was the town doctor, and so there's a museum to sort of what it was like to practice in these small environments. And it's really interesting, because when I go with my dad, he'll be like, oh, yeah, I remember going into his kitchen and getting a tetanus shot when I stepped on an ale when my dad and I were working on the barn. And this kind of thing, and he was so part of the life of everyone who was in that town and near that town. And now we look back at that as a quaint but lost time. You know, so it does make me really interested to think about how a technology like AI that many of us are afraid is dehumanizing actually may have the opposite effect in medicine. So tell me more about that. That's exactly it. And so I will tell one story. When I was at Nantucket, Cottage Hospital, there was a day where one of my patients came early. And when they came early, I was at a little place actually having breakfast. It was a lemon press for those who know. And I was having breakfast. And all of a sudden, my breakfast came out, but it actually came out in a takeout bag rather than kind of coming out in a plate. And I was like, why? And they said, oh, the hospital called Doc. And one of the guys who drive the taxis had come around. He was waiting out front already. They had already packed my bag. They gave me my breakfast and they shipped me off to the hospital. So I could see, you should say, seven years old, right? See the woman who would come in at the wrong time. And then have my breakfast there. And I thought, this is it, right? This is what I want to do. But then you think about what keeps me from doing that. And what sometimes keeps me from that is the fact that I actually need to figure out what's happening with that woman. So I need to know all of her past history. If she's new to me, I need to go through her electronic health record. Any paper records she may have. If it's somebody, not necessarily younger, but if somebody who, you know, wears wearables and other things, that's a valuable information to cardiologist, there's a lot of data, right? About their diseases. A lot more data than there ever was before. And so that's extraordinarily important as well. And so how do I get all that data in the 20 minutes that I'm kind of sitting there with her to provide the best care that's possible? And that's actually where AI can come in. Back in the 70s, we only knew so much about cardiac diseases. And it was all in your head as a doctor, right? But now there's a lot more to be known. How do I give the best care? I need AI to tell me the things that are relevant about her and put them together. So I can deliver the best care possible. The other thing I want to do is I want to talk to her. I want to be able to do this with her and not turn my back and be typing on the computer, right? And so AI for things like actually being able to take the notes and create them as it's listening to me speak. We call it voice to text. So that I'm not typing. I'm making eye to eye contact. I'm holding her hand if need be at the same time that my notes getting done. You know, that's really the kind of things that we think about. And that's not AI like Iron Man. I love Iron Man, by the way. But that's not AI like Iron Man. That's just how can I provide the best care? How can I give my patient the best attention? And I think that's what's really important. So thank you for those use cases with AI. And I just want to point out with all the funding in AI, how can academics and researchers hold the line on ethical and responsible uses of AI? Like what role can they play in insuring like equitable and fair AI for all, especially in areas as critical as healthcare? The challenge is, you know, we say equitable AI responsibly. And that's right. The AI itself needs to be a good algorithm. We need to use it responsibly. But at the end of the day, it's actually the data that's most important that the AI is using. AI is a tool. And that AI is making assumptions and making predictions based on data. So it's our job as, you know, all of us, the whole community, it's not just academicians, it's also industry, it's also governments, to make sure that our data represents the people who are supposed to care for. And if we can do that, then the likelihood that the AI is going to introduce no bias, yes, there are ways that algorithms can do that and go astray. You have ways to embed checks into AI to make sure it's doing the right thing. But when we as a community are talking about, oh, is AI going to be ethical? Really, the key thing is first, AI doesn't just work on its own. It works on data. Is data representative what we want to do? Do we believe that data is fairly saying the things that we say is everyone included in the data? That's the most important part. So I just want to make that distinction. But it's really the data. And then the AI, yes, we have ways to embed to make sure that the AI is doing what it's supposed to. Well, thank you for reminding us that AI is just a tool, because I think at the advent of the internet, you know, people were quite concerned. But HIPAA is still HIPAA. Privacy laws still exist. We're not going to have, as you say, RoboCop or Ironman robot doctors. And so its doctors still leading the conversation. But, you know, part of our job on this show is to mitigate the fear around AI. So thank you for really framing it again in that space that it is. It's a tool. Yeah, it really is. And, you know, I don't think we should be scared of Ironman, if you will. Again, he's my favorite. My kid loves Spider-Man. By the way, Tom Holland is like their thing, and I'm on the Tony Stark side of life. But you want Ironman as your doctor, actually, maybe not him specifically. But you want a clinician who's able to use AI in order to use all the data available to provide the best care. You don't want a clinician who's guessing and remembering the few things that they learned. Right? Now, the ideal is the clinician who has learned a lot, has clinical acumen, has experience, and then can use a technology. That's ideal, right? And I think that's what we're aiming for. And then there's nothing to be scared of. No, that's perfect. It's like you wouldn't want your accountant using an abacus, right? But you... I love... I'm going to use that analogy in the future. I literally am going to put an abacus on my next slide that I present. I want to run with it. I know you're a good teacher as well. Thank you. That is a good one. Okay, so I love this so much. And do you remember... I don't remember which alien movie it was in. But do you remember when Sigourney Weaver had to put herself in the robot surgery pod? Remember that? Yeah. It just sort of scanned her whole body and figured out what she needed and gave her the surgery right there. Like, I don't know if that'll ever happen. Anyway, that's a non-sequitur. But I do think about... Thinking about science fiction land. When I think about the data, I think I'd love to dig in on that a little bit if you wouldn't mind. So, um, you know, if... If like us, we've had, you know, experience in... in the field or a little bit or... I have just a little bit of public health background. So have tangential kind of interest in this space. But we don't always know that the studies that are being done, that give us certain indications on what to do with disease or with different... medical situations are not always done on a broad array of people. And I know one area where that's come to the forefront and I'd love to hear you talk about it is, heart health and women and heart disease and women. So, could you maybe educate us a little bit on what the data looks like now for how we look at heart disease and women and then potentially where AI might be able to help accelerate some of that research or understanding of heart disease and women in particular? Yeah. So there are a few things. The first is we're doing much better just by naming it and recognizing. So I think that's step one. Number two is, as we start to enroll more female patients in trials, what we also recognize is we need more women as investigators as the people doing the trials. And this is true for anyone. If you have people who look like you running the trial, you are more likely to participate. If you have people from diverse backgrounds running the trials, you're more likely not to forget anyone. And so I think that's a big part of it is not only enrolling more people and getting out there, but having the people running the trials look more like the people we're trying to get into them. And so that's really important. Now, what can you do with AI? Well, first of all, you have to go find the people and you have to train them. And so we have a clinical trials research program at the American College of Cardiology. We will actually bring in people who work in underserved areas, women, which we don't have as many clinical trials who are women, we'll train them what to do so that they can go back and do more of this work. But AI and your own public health so you know, Carla, AI does help us with population health. How do we find the patients that are right for certain trial? If you rely on each nurse or doctor out in the community to know all the trials available, it's not going to happen. You can give them tons of sheets and stuff to look at, but the handouts don't help. I was meeting with a company this morning for breakfast. And what they do is they use AI and it's some a version of a large language model like the chat GPT, but it's called it's called rag and it's when you you decide what you want to build into the model. Right, so you have controlled the data. And they use it to actually help find patients that are eligible for trials. And so now instead of taking six months to enroll the right number of patients, you've done it in three weeks because you found them faster. Why is that important? Well, first of all, it moves the research along faster, but more importantly, why is that important? You get the drugs to the patients sooner in the overall market. And so those are the kind of places where AI can help us with efficiency, with finding patients with doing things quicker and more efficiently than they did before. But at the end of the day, we still need to do the human work of walking around and finding the people who want to do this and then train them to do this, right? Great hats for people to do that work. And it probably gives agency to the patients as well because, I mean, unfortunately, I haven't had to be in a situation where I was, you know, hoping to find a, you know, medical trial or a drug trial that I could take if I needed it, but that must be a very stressful and exhausting experience. So if using these new tools to help match you to what you need for your particular disease, I mean, that must give a lot of agency to patients. Absolutely. You know, my husband and I are both in the medical profession. And when we had family members with cancer, which is not either one of our professions, and we had to figure out, are there trials? What can we do? It's exceedingly hard. Unfortunately, we knew people who knew people, and that's the only way we got information. Majority of the world doesn't have that opportunity. So again, I love this concept of patient agency. And I'll tell you how I use it in a slightly different way that has to do with AI in just a second. But the concept of patient agency, meaning like, if there are trials that you're eligible for, you should know about it. And we have the way to find them. Those trials for you, that's really important. The way I think about patient agency is a little different because I'm a cardiologist. You hear a lot about wearables. My blood pressure said, you know, my heart rate was this, and people are wearing them, and they're bringing this data in. In the clinical world, when you're in a office, and you're seeing patients, and they bring sheets upon sheets of all of the things they're measuring, it's really hard. You only remember, you only have those 20 minutes that you were originally talking about to really take care of their health. Now you have these sheets, and you don't know what you're responsible for. Now, what patient gave me something, what if one of those sheets is something dangerous? What if one measurement, right? So that's the place where it's actually really important for us to start working as clinicians, patients, and then the industry, the consumer industries that make these kind of wearables. And we have to work together to say, hey, consumer brands, you need an infrastructure and a platform. We can't just have them printing things out. I need you to catch what's high, what's low, what their baseline is. That's your responsibility to give that to the patient and to me. And then I have to say it's not consumerism. It's patient agency. These patients want to know their numbers. Why am I stopping them from knowing their numbers? But I need help, because otherwise it's too much data. That's where AI comes in. What is your baseline, Anna? Because it's different than Kara's baseline, whatever, heart rate, blood pressure. What do you live at? And then when are you out of range? And you then understand what put you out of range in your lifestyle or are there meds I should do? Those kind of things, that's what AI enables. And so, you know, it's not consumerism. It's patient agency. And I think things like wearables are really important also in addition to the data for us to start letting people measure themselves. Because there's so many people in our country who are just not getting healthcare. So what are we saying? Like, because you're not getting healthcare, but you can't get the gold standard because there's no clinician there. You shouldn't get care. That's not the right answer. The right answer is we've got technologies. We've got data. We've got AI. How can we optimize them to get everybody care as we're working on the problem of not having enough doctors for instance? Well, I really appreciate that you're walking the walk with education. I know that's a big part of your focus. And I appreciate that. You know, for the listeners out there, I want to encourage you to really check out Dr. Botswraza May and what she's working on primarily in education's huge. You know, my father passed away from cancer as and as you highlighted, you know, if I didn't have doctors in my family, we wouldn't have been able to care for him. He didn't have medical insurance. And therefore, I got to have a firsthand view of, you know, I became his hospice nurse basically, which as anyone who knows, you can't really mess that up. But he had an excellent treatment plan and thanks to doctors, both my brother and I and my father and law, that process went smoothly. But, you know, thank you for reminding us that where we're heading towards patient advocacy and education, I mean, I'll fully admit it was in somebody's TED Talk that I realized there's such a thing as numbers. And I thought, I'm so scared to find out what mine are. And I think that one of the reasons why heart disease is so deadly in women is we just lump it. You know, we we feel something wrong and we go, I don't have time to be sick. I'm holding line with children and maybe parents or care for, you know, everybody in the family. So again, I'm bringing it back around to you. Thank you for this education side. And maybe that's, you know, something that everyone can look forward to within with an AI technology or a wearable. I mean, any any other thoughts on that and I really appreciate you unpacking this deeply. Yeah, you know, having your numbers is so important. Understanding them is even more important, right? One of the things I think AI is going to enable us to do, you know, we have chatbots for everything now. And so are there ways in which groups like the American College of Cardiology can create education for patients that they can then understand what they're looking at? And so we've always made, we have a brand called Cardio Smart. We've always made infographics, right? And information that we can share. But is there a future, I hope so, where we can have an interactive chatbot where you can ask a question and you could reliable answers. Now, let me tell you the risk of that is you have to control the information going in. You have to express it the right way. And then you have to have an outlet for patients to be able to get more information or get a better explanation if they didn't get it. So your clinicians have to be aware or family members should be aware that you're learning like this. The other day, I was using an airline industries app and I said to my family, you know, that was just the nicest experience they were so sweet. And then I thought to myself, there's no they there. It was a chap, that was a computer talking to me. And I, who do this for a living, I was like, oh, that's such a nice chatbot. It's not nice, right? But it's designed to be that way. But now, thank you, our patient. And instead of coming to the ACC and to, you know, Anna and Kara and Ami said, this is a reliable site, you just go to whatever. And they seem really nice. That site isn't responsible for any hit by a privacy. They can share whatever you ask it. They're not responsible for your health. Something goes wrong from what they did. They're not a healthcare organization. So that does worry me. Is that accessibility of anybody kind of answering questions, right? But if we can create and distribute education from reputable sources, direct to our patients and maybe do it by partnering with the wearable company, right? The wearable company should say, hey, we partner with the ACC. And therefore, the education you're getting is like this. Now, that's a nice ecosystem we're creating for our patients. So I do think we have a lot more responsibility to the patient that's coming in the future as well. Right. And I'd love I to hear more about so what you're doing at the ACC and what the role of chief innovation officer is doing at the ACC. So it's the American College of Cardiology. And that's just one of your many jobs, right? So the American College of Cardiology is actually a global organization. It's two thirds of our members in the US, one third or actually global from 42 different chapters in countries. And that's 57,000 members. So there's like 500 people who work at our company. But 57,000 members, 2,500 health systems. So it's large. We do a lot of things. We mainly create a lot of education, written education, written print journals, meetings, education for nurses, administration cardiovascular doctors, trainees. We actually also educate residents, med students, high school students and medical school students. So we go all the way down because we know that we need a pipeline. We have a shortage of doctors and nurses coming up. And so we do a lot of education, but we also do advocacy on the Hill for the things that we think are really important for our patients, for how they get covered, for getting health care in the community where you live. That's hard. And sometimes we need a central mechanism to get that done at a governmental level. We spend a lot of time with registries and quality. We carry the largest cardiovascular registry, which is anytime you're getting a procedure, you want your team to be logging that procedure up against other people's procedures to make sure that team stays as good as they can, learns where some of their gaps may be and improves upon them. So you want to know that that's existing and that's kind of the service that we provide and do together with clinicians and teams. And so those are just a few of the things. And we have a large global arm as well that really thinks about both the areas abroad, but even our areas in terms of getting health to the areas that need the most. I was just on rural health collaborative radio the other day. And you know, so important cardiovascular care in our rural areas, we've got a shortage and we need to utilize data and wearables and technology and AI to really help with care there. So maybe I'll end with one of my favorite things that we're working on, which is how do you use AI to upskill people and give them the information they need to provide care because not everybody can train for 35 years, like I did, by the way, it was like really close to me. And they're like, we weren't sure if my husband's PhD, my daughter's kindergarten, or like my being done with training was going to happen first. Like it was neck and neck for a while. But we can train people for 35 years everywhere. And some people, yeah, don't have access. So how do you take the local pharmacist? How do you take the local community health worker? Whether that's rural America or that's global and say, look, I can give you the knowledge you need at the point of care. You can use this app. You can ask questions, you can get information about that disease. And it can be reliable. Or, hey, you can use these monitors on your patients. And they're going to, again, like we talked about before, identify when something is wrong versus not wrong. We're not asking for any quiz and answers sometimes. We're asking for triage. Get people before they get too sick. And I think with that in mind, there's nothing to be scared of with data and AI as long as you're keeping the patient at the center. And you're remembering that the key thing we can do with this is we can offer you care earlier in the community where you live while you're living normal life, rather than having you have life threatening events, which we could have seen coming now with this technology. I am so glad that you brought it full circle, because we can really understand you're thinking globally and you're acting locally. And I'm so honored to have this conversation with you, Dr. Bot, because I feel that to your core, you embody that Norman Rockwell picture. And thankfully, someone like you is really at the helm of so much and so much exciting research. And again, thank you for making AI seem less scary and really putting it in the lane of a tool that it is. Well, thank you for having me. I'll have to tell you on the past couple of weeks, I've been at some amazing Boston innovation events. We have the best ecosystem for innovation here. And that's true for biologic things, for pharma, for devices. And it's just so exciting. And what I've noticed is there are a lot of different people in the room now. It used to be tech guys, we need tech guys or girls. And now we have cross-pollination, you have clinicians and engineers and finance people and journalists all in the same room trying to understand the same problems and then figure out where do I fit in this story to make things better. So I'm super proud of our Boston innovation ecosystem. I'm really, really proud to be part of it. I love that. And we're proud to report on it. So thank you for taking us home. We have had a wonderful chat with you. We look forward to lots of new innovation. And from the mecca of tech learning and all things good, thank you for being on our show today. We really appreciate you, Dr. Bot. Thanks for having me. Thank you for joining us on Building AI Boston. Stay tuned for more enlightening episodes that put you at the forefront of the conversations shaping our future.
