YouSaid · the spoken record

Vijay Pande

lines on the record: 76
first: 2019-06-13
most recent: 2019-06-13
sittings or episodes: 1
sources: 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

“Well, I mean, I think one of the things we've harped on is that you've got to have human oversight. We can't trust an algorithm absolutely for any serious matter. Because if we do that and it has a glitch or it's been hacked or has some kind of adversarial input, it could hurt people at scale. So that's one of the things that we got to keep an eye on. For example, if an algorithm gets approved by the FDA, oftentimes these days it's an in silico retrospective sort of thing. And if we just trust that without seeing how it performs in a particular venue, a particular cohort of people, these are things that we just shouldn't accept blindly. So there's lots of deep liabilities and it runs from, of course, privacy, security, the ethics, how many aspects that are not ideal about this. But when you think about the need.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Right. I think that's really what is going to be one of the big early changes in this new AI medical era is that diagnosis is going to get so much better. Right now we have over 12 million serious errors a year in the United States. And they're not just costly, but they hurt people. Yes. So this is a real opportunity to upgrade that. And that's a much more of a significant problem than most people realize.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“When I think about what ML or artificial intelligence AI could do, there's two axes. There's one's like just scale, like the fact that you can scale up servers on Amazon trivially much more than you could scale up human beings. We could scale up a thousand servers right now or 10,000 servers right now. I don't think we could call 10,000 doctors and get them here. The other thing you could do is that you could sort of talk about how the access is like sort of intelligence or capability. And you're talking about both in a sense that you can scale up not just the fact that you could have like a resident or a med school student sort of doing things and having a lot of them. But you, in addition to that, you have”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Exactly. You know, it brings in the integration of what would be the ground truths of thousands for that particular data set. So I think it has a potential. And of course, a lot of this stuff needs validation, but there's a lot of promissory studies to date that suggest that's going to be very possible.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“No, it's so true. And that gets me to Daniel Kahneman's book about thinking fast and slow and the system one that is the reflexive thinking that happens automatically versus what we want are reflective thinking, which is system two, which takes time. And it turns out that if a doctor doesn't think of the diagnosis of a patient in the first five minutes is over a 70% error rate. And that's actually how much time is the average with patients. So we have the problem, as you've alluded to, of kind of a plateauing early on in the career, but we also suffer because of lack of time with the system one thinking.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“We're talking about radiology here in pathology, but I mean, we could sort of think about this as an issue for diagnosis in general. And there's one thing you pointed in the book, I think really beautifully, you know, you said once trained doctors are pretty much wedged into their level of diagnostic performance throughout their career. That's kind of an amazing thing is that doctors, I guess, go through CPN and so on, but you only go through med school once, and that's an intense process you learn a lot, but you can't go through med school all the time.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“The pathologist, you know, they have remarkable discordance when they look at slides. And to be able to have that basically looked at as if hundreds of thousands of them were reviewed, getting back to your second, third, and nth opinion, to get that as input for them to help consult with a patient, I think is really a bonus.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“In that case, it almost seems like everybody is better off. The doctor is better off because the pathologists are not just looking at slides, but actually is dealing with patients. And presumably the patient's better off because you have these false negatives get found.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“That Saurab Jah, who is a radiologist at Penn, he and I penned a Jama editorial about the information specialist, radiologists and pathologists. Their foundation is reviewing patterns and information. But what's interesting is this is an opportunity for them to connect with patients because they don't. Right now, radiation never sees a patient. Radiologists live in the basement. The pathologists look at the slides, that group of pathologists. But they actually want to interact with patients and they have this unique insight because they're like the honest brokers. They don't want to do a surgery. They want to give you their expertise. And so I think that's what we're going to see a pretty substantial change. And as you touched on this new specialty, it'll look different than the way it is today.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“And so that seems to be a theme running through the book. So for the first half, in terms of the understanding, what do you think that's going to look like? I mean, one of the things I've been constantly wondering about is whether there'll be a new medical specialty.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Somebody's going to need to interpret the algorithm, sort of be on top, and that, in a sense, the doctor is freed from the stuff the doctor shouldn't be doing. The BS accounting or the typing and all these things. And that's not the best use of doctor's time. And it's funny because it seems like the best use of doctor's time is in understanding what these tests would mean, whether it be an AI test or cholesterol or whatever, and in how to communicate with the patient.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Algorithms with ground truths that are trained on hundreds. But then, of course, you've got that overread by the trained radiologists. So there, you know, I think that's an example of how we can use AI to really rev up accuracy.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“The ground truth when it's applied to training an algorithm, of course, is knowing that it is the real deal, that it is really true. And I think a great example of that is in radiology because Radiologists have a false negative rate of thirty two percent. False negative, and that's the basis for most of the litigation in radiology, which is over the course of a career, a third of radiologists get sued, mostly because they miss something. So what you have are...”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, here I'm really curious because what is the ground truth? Because generally we don't trust an individual person as knowing everything either, right? So the ground truth would be like a second opinion or third opinion or a fourth opinion or even like a board to look at something. And that would be what I think most people would view as the ground truth.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, well, that's, I think, where the complementarity, the synergy between machines and people is so ideal because we just have early satiety with data. Whereas deep learning has insatiable appetite. And so that contrast. But we have, as doctors and humans, we have just great contextual abilities, the judgment, the wisdom experience, and just the features that can basically build on that machine processing because we don't ever want to trust an algorithm for a serious matter. But if it tees it up and we have oversight and we fit it into that person's story, that I think is the best of both worlds.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“In the future. Well, and this is one thing that computers can do very well is logistics and coordination. There's tons of cases where you might, like thyroid cancer, we're just talking about maybe you have to bring in an endocrinologist in addition to an oncologist. And it's shocking that often there's no discussion there, there's no communication, but yet the challenge in my mind is how does a computer magically know things that we can't do right now?”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Right. Well, I think there is getting arms around a person's data, this whole deep phenotyping. So no human could actually integrate all this data, not only the whole electronic record, which all too often is incomplete, but also pulling together sensor data, genomic data, gut microbiome, all the things that you'd want to be able to come up with not only better diagnoses, but also the better strategy for prevention or treatment. So I think what's going to make life easier for both doctors and for the patients is having that data fully processed and distilled in the book. I tell the story about my knee replacement and how it was a total fiasco. Part of that was because my orthopedist who did the surgery wasn't in touch with my congenital condition. That hopefully is going to be something we can transcend in the future.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“We could bring in other technologies, right? We've thought about just how imaging or other type of diagnosis comes in. And we've seen all these cool things about how machine learning can improve this, but then also it's funny because at the same point, and you bring this up in the book, that overdiagnosing also can be very difficult. It was very stunning where you talked about how the incidence of thyroid cancer is going up, but the mortalities went flat.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Oh, that's all part of that conversation because you say, well, you know, Mr. Jones, we're going to have you have the lab test for such and such. And then we're going to, you know, get this scanned and it's all done through the conversation.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“And so I'm imagining like what that doctor Viz is like then. So we've got maybe NLPs so the doctor doesn't have to be transcribing and not interacting with Epic. Who knows what's in the back end but doesn't even matter anymore.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Exactly. So the notes that are synthesized from the conversation are far better than the notes that you would get in epic or Cerner where 80% are cut and pasted and they're error-laden. So, I mean, just this week, Google AI published in JAMA of their experience. I think it's really going much faster because the accuracy of the transcription and the synthesized note is far better than what we have today and it exceeds professional medical transcriptionists in terms of accuracy.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Alexa's a very basic version of voice recognition, but you're talking about something much more sophisticated now, something where they're actually doing NLP, they're doing transcriptions that doctors don't have to take notes. If you were more sophisticated, you could put an ontology onto this such that you're not just getting like a transcript of what's going on, but that you have very machine learning friendly organized data.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, I think that is a kind of fundamental of the problem of, you know, doctors not even making eye contact. And as a child, to draw that picture, how unnerving that was her trip to the pediatrician natural language processing. Can actually liberate from keyboards. And so it's already being done in some clinics and even in the UK, in emergency rooms. And so if we keep that up and build on that, we can eliminate that whole distraction. Doctors and nurses and clinicians being data clerks. I mean, this is ridiculous. So the fact that voice recognition is just moving so fast in terms of accuracy and speed is really encouraging.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“More productivity, but you know, I think you put this on Twitter where it's like some kid drew like a drawing of going to the doctor and the doctor, the picture was the doctor with their back turned working on a computer. And, you know, that is what happens too much. But yet we're talking about technology coming in. So how does this all work out that more technology means less computer”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Exactly. That gift of time, the human side, which is the center of medicine, that's been lost. The big business of healthcare and all of its components like electronic records and relative value units and all this stuff basically has sucked out any sense of intimacy and time. And it's also accompanied by lots of errors. But of course, it's not a gimme because administrators. Want more efficiency, more productivity”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, that's really what I was pondering and I really did this deep look into AI. I actually didn't expect it to be this back to the future story. Yeah. But in many ways, I think it turns out that as we go forward, particularly in a longer term view, the ability to outsource so many things with help from AI and machines, I think is going to get us back. It could. It could. That's the big if to where we were back in the 70s and before.”
2019-06-13 · a16z Podcast · a16z Podcast: AI and Your Doctor, Today and Tomorrow · IDENTIFIED FROM THE TRANSCRIPT · source