YouSaid · the spoken record
Vijay Pande
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- 76
- first
- 2019-06-13
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- 2019-06-13
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- 1
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- podcast
Every line below is reproduced as it was said and linked to the record it came from. Nothing here is summarised or generated. Directory · Search · Corrections
“You know, you talked about Back to the Future. There might be another sci-fi analogy. I actually think there's some Star Trek episodes like this where actually the group that has the highest technology is the one where the technology is invisible”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Not the part I needed to be done. When you're dealing with analog tools and they can be so superseded by the things we have today and when you're sharing them with the patient, so here's what you have. And then you send them the video files or the metrics so they can look at, you know, when they get home and get more familiar with their body. It's not only the physical exam that happens instantaneously in the encounter, but the ability to have that archived data that people get more they learn about themselves. That's all part of that awareness that's important.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“So the tools of the physical exam may change, but the actual hands-on aspects of it and the interaction with the person, the patient, and that that's the intimacy. And we've lost that too. You know, the physical exams have really gotten very much a detraction from what they used to be. I mean, we need to get back to that. That's what people want when they go see a doctor.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“No, no, not at all because human touch. So when you go to see a doctor, you want to be touched. That's the exam part of this. People, when they get examined for their heart and you don't even take off their shirt, they know. They know there's a shortcut going on. They want to have a thorough exam because... They know that that's part of the real experience. And so what we're talking about is the exam may change. Like, you know, for example, I don't use a stethoscope. I use a smartphone ultrasound and do an echocardiogram. And I show it to the patient together as we're doing it in real time, which that person would never see. And by the way, they wouldn't know what Lub Dub looks like, but you sure can see or sounds like, but you sure can show them. Yeah.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Let's go back to where we start a visit to the doctor in the future. And the good news is that the doctor doesn't have to do any of the typing or the recording. AI's sort of figuring out the diagnosis and that the doctor has all the time now to actually be empathetic and communicate, which is great. But is that now all that's left?”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, well, you're bringing up a big hole in the story, which is multimodal data processing. We are not doing it yet. You know, like a perfect example is in diabetes, people have a glucose sensor and the only algorithm they have tells them where the glucose is going up or down. That's pretty dumb. Why isn't it factoring in everything they eat and drink and their sleep and activity and the whole works someday we'll have multimodal algorithms, but we're not there yet.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“But if you combine all these things together, you know, this thing where you're monitoring your body every five minutes and your diet and your exercise and your drugs. And you have all this longitudinal data. That's something that no one's ever had before.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“I think it is because there you could improve the efficiency if you knew who are the people at the highest risk and who you want to change the natural history, what their algorithm is predicting, if it's something that's an adverse outcome. So eventually we'll probably get there, but it isn't nearly as refined as the other areas.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, that's a part of the problem, too, is that the studies that have been done to date, things like predicting Alzheimer's, predicting all sorts of outcomes you can imagine, they're not with complete data They're just taking what you can get, like what's in one electronic health record, one system, rather than everything about that person. So maybe it will get better when we fill in the holes.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“You're going to tell a person about a prediction, you know, we're not very good at that. When we talk to people with cancer and we tell them, you know, their prognosis, it's all over the place in reality. And so, you know, the question is, our algorithms really going to do better, or are they just going to give us a little more precision, maybe not much?”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“I'd call that a real soft spot in AI. And I told the story of my father-in-law, who kind of was my adopted father in the book about how he was on death's door. He was about to come to our house to die. And he was resurrected. But any algorithm would have said he was a goner. And so the idea that at the individual level you could predict accurately, whether it's end of life or when you're going to die or in the hospital, this is how long you're going to stay or you're going to be readmitted, all these things. We're not so good at that. We can have a general sense from a population level, but so far prediction hasn't really panned out nearly as well as classification, diagnosis, triage, that kind of stuff. And I still think that that's one of the shakier parts because then you're...”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, so like you talked about it could look at the whole cardiogram. It could look at things that we don't look at because either we're expert enough to know that couldn't possibly ripe even if it is. Or we just don't have the time. It reminds me sometimes these algorithms almost like children in that kids just don't know until they'll try things. And that's where imagination and creativity often comes from.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, Yeah, well, the unsupervised learning is interesting because you can finally just, you know, and for those who aren't familiar with the term, it's kind of like trying to find the clusters to sort of not have the labels, but to see the lay of the label.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Right, well, if we get into heavy into unsupervised learning, we're a bit limited by the annotation and the ground truth going back to that. You can only imagine things when you have those for supervised learning. But, you know, as we go forward, we'll have more of those data sets to work with and we'll be better at going forward without, well, with federated data sets and unsupervised learning. So the opportunities going forward are pretty enthralling.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, you know, this may be the most important point is that we have to start having imagination because we don't even have any idea of the limitless things that we could teach machines. Because I'm getting stunned almost on a weekly basis. I never would have thought of that. And so just fast forward. Here we are in 2019. What's it going to be like a few years of all the things? When the Mayo clinic told me they could look at a 12-lead cardiogram for millions and be able to say this person's going to get atrial fibrillation in their life with X percent probability? I said, really? And they've done it. And so I never would have expected that.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Imaging plus genomics, where the genomics readout, let's say, or whatever the blood assay is the gold standard, I don't want to predict what the pathologist would say. I want to predict the biopsy. I want to predict the blood or whatever, the true gold standard is behind it. And if you're training on the best labels, you can do things that no human being could do.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“So then you make a good point because I think it's tempting to just try to do what the human can do better or what the human can do better now try to do as well. But now you're talking about doing things that no human being could do.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“But you could actually train the algorithms so that when the pathologist is looking at it, it's already giving you what is the most likely driver mutation. It's incredible. And that does get me to touch on the deep science side of this, which we aren't recognizing is way ahead of the medical side, the ability to upend the microscope. You don't have to use fluorescence or H&E. You just train. So you forget staining. The idea that you used to be hard to find rare cells, just train the algorithm to find the rare cells. I mean, we're seeing some things in science, no less in drug discovery, in processing cancer and sequencing data, and certainly in neuroscience. It's a real quiet revolution that's much further ahead than on the medical side because there's no regulatory hurdles.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“One of the scariest stories I saw was that this algorithm was getting cancer no cancer right with crazy high accuracy. Like AUC of like 1.0, like never making a mistake. And it turned out that there was some subtle difference between like a high Tesla magnet and a low Tesla magnet and that the patients who were very sick to start off with were always getting one type of scan. And that a human being couldn't tell the difference, but that the machine was picking up some signal not of whether it was cancer or cancer, but whether they were getting like the fancy measurement or the less complicated one. Or another great example is there's a classic example where they're, I think, predicting tumors and they had rulers for the size of the tumor on all the tumor ones. And so really ML was a great ruler detector.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“So then they nailed it. So, the whole idea is that the biases that we have that are profound. But when you start debiasing both the data scientists and the doctors, the medical people, then you start to get a really great result”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“We need machines and people to get the best of both worlds. So in the book, that example of how we crack the potassium case between Mayo Clinic Cardiologists and AliveCore data scientists. And what was amazing about that experience to review with them was that the cardiologists thought you should only look at one part of the cardiogram, which historically known the so-called QT interval, because it was known to have something to do with potassium. But when that flunked and the algorithm was a farce, the data scientists said, well, why are you so biased? Why don't we just look at the entire cardigram? And by the way, Mayo, you only gave us a few million cardiograms. And why don't you give us all the cardigrams?”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“On average. So, if you think about how all this has to actually happen, now we talked about what's possible, but if you get to nuts and bolts, it's interesting to think who's going to do it. Because if you take just a pure data scientist who doesn't understand the medicine, I don't know if that would be enough, right? But also, I don't know if you could take a doctor that doesn't understand data science, right? And so is it going to be teams of commingled groups that get this together? Because there will be iterations between the data science and the biology and the clinical aspects that have to come one after the other to be able to make these advances.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“The main thing those are commonal infections from the hospital, but other medication errors and other things, the comfort of your own home, you can actually sleep, you be with your loved ones, the convenience, but most importantly, just think of the difference in expense. You could buy years of broadband data plan.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“The resistance we have to anticipate is going to be profound. One of the problems is that the medical profession, it may not be ossified, but it's very difficult to change. The only changes that ever occurred rapidly, like adoption of robotics and surgery or because it enhanced revenue. Now these are none of these things are going to enhance revenue. They're actually going to potentially be a hit. We have all these interests. that this is going to challenge. Like for example, we could get remote monitoring of everyone in their home instead of being in a hospital room unless they were needing an intensive caring. Now, do you think hospitals are going to allow that to happen? because they would be gutted and then they won't know what to do with all their facilities. So the American Hospital Association is not going to like this.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“No. And it's intriguing because I think there's a chicken and egg problem here because I think first this has to be put in. Often in these, any big changes, there may be resistance. Who's going to be fighting this?”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“More depressed. So we have to break that up. And I think if we can get people, so there's time together and that real reason why the mission of healthcare is brought back. We can do this. It's going to take a lot of activism. It's not going to be easy. And it's going to take a while. But if we don't start planning for this now, it's not going to happen.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“A lot of simple things, ear infection, skin rashes, and all that sort of stuff that's not life-threatening or serious, but it's bypassing a doctor potentially almost completely. So between this flywheel of algorithmic performance enhancement, if we stand up for patients, then we have all this time to give back. Once we have time to give back, then we tap into why did humans go into the medical profession in the first place. And the reason was because they want to care for their fellow human being. But they lost their way. And now we have the peak burnout and depression and suicide and the history of the medical profession. And by the way, not just in the US, you know, in many parts of the world, and how are we going to get that back? Because it turns out if you have a burnout doctor, you have a doubling of errors. And it's a vicious cycle.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Up, and if we say that time, all that benefit of the AI part, the machine support, and by the way, that's also at the patient level. So the patients now, with their algorithmic support, they're decompressing the doctor load too. Yeah, yeah.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, we are missing that in a big way today. And how do we get it back? Well, you know, I think how we get it back is we take this deep phenotyping, we do deep learning about the person, and that's all outsourced with oversight for a doctor or clinician. Now, when you have this remarkable improvement in productivity, in workflow and efficiency and accuracy, all of a sudden, you have the gift of time. If we just lay down as doctors have over decades for administrators to go ahead and just drive revenue and basically have no consideration for patients or doctors, we're not going to see any growth of empathy. We're not going to see the restoration of care in healthcare. But if we stand”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, so one other area that I thought was really intriguing, and to me, this was almost paradoxical, the concept of AI being useful for empathy. Because I would have thought like if we're thinking about the things that a computer is good at, like multiplying numbers, that's going to be something like they're going to beat humans of that any day. I would have thought, though, that empathy would be the one, like the last bastion of what we're good at. And what the computer is good at, but how does AI get the empathy? Because as we started the conversation with us about how that's a key part of what a doctor does, but like what can AI do there?”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, it's Yeah, no, exactly. And then there's this contrived aspect of going to see the doctor where a lot of people find that very stressful. And when we talk about white coat hypertension, we don't even know what normal blood pressure is because we need to check that out in thousands, hundreds of thousands of people in the real world to find out what's normal. We've already had this chaos of American Heart Association saying that they changed the blood pressure guidelines on the basis of no data. Speaking of lack of objective metrics.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, it's a one off. And so it's a funny thing because people wonder about, let's say, the knock on a wearable will be that it's not like an eight-point EKG or something like that. But on the other hand, it's there with you all the time.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Metrics of one's mental health as a cardiologist. For all these years, I'd have these patients, they'd come and tell me, I feel my heart's fluttering. And I would put in the note, the heart's fluttering. That was so unhelpful. Now I can say, well, you know, you should be able to record this on your phone or if you have a smartwatch. And when your heart flutters, just send me the PDF of that. And we have the diagnosis. That is real world no longer subjective to a whole different look, really. And by the way, the patient who has the fluttering, who records their cardiogram, they don't have to wait for me. They already have an automated read from AI that's more accurate than a doctor.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, as it turns out, that was kind of old medicine where we just talked about your symptoms. But new medicine is with all sorts of objective metrics. So a great example of this is state of mind or mood. And that's going to transformative for mental health because now everything from how you type on your smartphone to the voice. Which is so rich in terms of tone in a nation to your breathing pattern, to your facial recognition of yourself. I mean, there's all these ways to say, you know, Vijay, you're really depressed. You know that you're depressed. So the point being is that you have objective.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Right, and so many aspects of it. Like, you know, now chronobiology is really this hot topic. That's about your circadian rhythm. And should you eat only for eight hours during the day? Well, certain people, yes, but, you know, the whole idea that there's this thing for everyone, we got to get over that. That's what deep phenotyping is all about to learn about the medical health essence of you. And we haven't had the tools until now to do that.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“And what I think is interesting about this is that it's something where we don't need the AMA or NIH or anything else to get involved in terms of diet. B, actually, people want to take care of these problems because I think most people are motivated. We just don't know what to do.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Take everything we just talked about, multiply by thousand or hundreds of thousand. That's how we learn here. And so what I think is the biggest thing about the AI underappreciation is the things that we're going to learn that we didn't know. Like, for example, another great example is.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, the problem, Vijay, is a number of levels and the sea of data. I mean, we're talking about terabytes of data to crack the case for each individual. So it's not even just your gut microbiome of the species of bacteria and their density. But now we know it's the sequence of those bacteria that are part of the story. Then you have, of course, these continuous glucose every five minutes for a couple of weeks. That's a lot of data. Besides that, you've got all your physical activity, your sensors for stress, your sleep data, and then your even your genomics. So when you add all this together, this is a real challenge. No human being could assimilate all this data. But what's interesting is not only at the individual level, but then with thousands of people.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, Aaron Segal. And now it's been replicated by many others and it's being extended. But what would be promoting your health? And right now it's these proxy metrics like your glucose or your lipids in the blood. But eventually we'll see how outcomes and prevention can be fostered by your diet.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“And I don't think you would prescribe that Exactly. And then it Well, I think that's central. If we didn't have machine learning, we wouldn't have known this. And only, you know, thanks to the group and the Wiseman Institute in Israel, they cracked the case on this. Iran.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“What's intriguing to me is that in cases, there are cases now, especially, let's say just glucose, where you can take technology developed for type 1 or type 2 diabetics. And now I'm not diabetic, but I actually had the sort of, I was about to say joy, but at least the intellectual intrigue of having a CGM on me for two weeks.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Almost all of it. I couldn't agree more that that should be a direction. We have had this so naive notion that everyone should have the same diet. And we never got that right as a country. But now we know without any question that people have an individualized and highly heterogeneous response. That's not just through glucose spikes. If you and I ate the exact same food, the exact same amount, the exact same time our glucose response would be very different, but also triglyceride response would be different. And they don't track together. So what we're learning is if you get all this multimodal data, not just your gut microbiome and sensor data and your sleep and your activity, your stress level, and what exactly you eat and drink, we can figure out what would be promoting your health. We're not there yet, but we're seeing some pretty rapid progress.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Maybe there's another solution we could think about, which you also point to in the book, which is what can we do to drive through consumer action? For instance, a lot of our healthcare is sick care, right? What happens when we get sick? That's almost all of it. What about what can we do to stay healthy? First thing I think of is diet and lifestyle, right? That could go a long way in so many diseases, so many things that we deal with. And so actually, you touch on diet before we're even talking about diagnosing whether you have cancer, should we be diagnosing what you'd be having for lunch?”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Childhood mortality, infant mortality, maternal mortality. The worst people don't realize that. Then you have the UK and so many other countries that are at the $4,000 per year level. And they have outcomes that are far superior. So if we use this, we could actually reduce inequities. We could make for a far better business model paradoxically, but we're not grabbing the opportunity.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“One of the problems we have that you're touching on is our professional organizations haven't really been so forward thinking. They mainly are centered on maintaining reimbursement for their constituents. Entities like NIH and SF and others could certainly be part of the solution. What you want to do here, I think, is to really accelerate this. We're in the middle of an economic crisis in healthcare, which is in the US the worst outlier. I mean, we spending over $11,000 per person and we have the worst outcomes. Life expectancy going down three years in a row.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Yo, well, we have no national planning or strategies. How is AI not only for healthcare, but in general, how is it going to be cultivated and made transformative? The experience I had in the UK was really interesting because there they not only have the will, but they have a whole wing of the NHS for education and training. Just think about it. We already talked about professions within medicine that are going to have a morph of their daily function. So we're not well prepared. Who should take a look at?”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“So, what should one do at that scale? There's various things people propose. Is this something to have a new national institute of health in this area? I think when I think about government playing a role, I think I want them to try to help them build the marketplace and set the rules. But we have to be careful that we don't put too much regulation as well. I mean, when you say we don't have a strategy, what's missing? What should we be doing? Yeah.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, yeah, then what are you going to get out of that? So we are at a handicap position in this country. And the other thing, of course, is we have no strategy as a nation. Whereas China, UK, and many other countries, they are developing or have developed planning and strategy and put in resources. Here, as a nation, we have zero resources. In fact, we have proposed cuts to the same granting agencies that would potentially help.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“And we have no data for each person. Basically, our data is just spread around all these different doctors and health systems. Nobody has all their data. And that is a big problem because without the inputs that are completely...”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, it is rolling out in other parts of the world. You know, I just finished this review with the NHS, and that was fascinating because they are really going after this. They are the leading in the world force in genomics. And now they want to be in AI. So they already have emergency rooms that are liberated from keyboards. And they are going after this. And this, of course, in the middle of Brexit. So that's kind of amazing. But China is really implementing this, that you could say, well, maybe too fast because out of desperation or need.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source