YouSaid · the spoken record

Regina Barzilay

lines on the record: 85
first: 2019-09-23
most recent: 2019-09-23
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

“Hospitals don't see much incentive to give this data away on one hand, and then there is general concern. Now, when I'm talking about societal benefits and about the education, the public needs to understand, and I think that there are situations, and I still remember myself, I really needed an answer. I had to make a choice. There was no information to make a choice. You're just guessing. At that moment, you feel that your life is at the stake, but you just don't have information to make the choice. And many times when I give talks, I get emails from women who say, you know, I'm in this situation. Can you please run statistics and see what are the outcomes? We get almost every week a mammogram that comes by mail to my office at MIT. I'm serious.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“But even today, there are already a lot of data which can be de-identified perfectly, like your test data, for instance, correct, where you can just know the name of the patient, you just want to extract the part with the numbers. The big problem here is, again,”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“And it's a mute removing the identification, removing the names of the people. There are other data, like if it is a raw text, you cannot really achieve 99.9%, but there are all these techniques that actually some of them are developed at MIT, how you can do learning on the encoded data where you locally encode the image, you train a network which only works on the encoded images, and then you send the outcome back to the hospital. So those are the technical solutions. There are a lot of people who are walking in this space where the learning happens in the encoded form, where still E. But this is an interesting research area. I think we'll make more progress. There is a lot of work in natural language processing community how to do the identification better.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“I think there are two things that could be done. There is a technical solution and there are societal solutions. So on the technical end, We today have ability to improve this ambiguity, like for instance for imaging for imaging you can do it pretty well”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“We all will benefit from all these insights. And it's not like you can say, I want to keep my data private, but I would really love to get it from other people because other people think the same way. So if there is a mechanism to do this donation and the patient has an ability to say how they want to use their data for research, it would be really a game changer.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“You know, they have a lot to lose if they give the data to the wrong person, but they may not have a lot to gain if they give it as a hospital, as a legal entity, as giving it to you. And the way, you know, what I would mention happening in the future is the same thing that happens when you're getting your driving license. You can decide whether you want to donate your organs. You can imagine that whenever a person goes to the hospital, it should be easy for them to donate their data for research and it can be different kind of do they only give you tests results or only imaging data or the whole medical record because at the end”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“Oh, it is already digitally stored. You don't need to do any extra processing steps. It's already there in the right format. Right now there are a lot of issues that govern access to the data because a hospital is legally responsible for. For the data”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I mean, the hospital may, you know, assuming that you're doing research collaboration, you can submit, you know, there is a proper approval process guided by RB. And if you go through all the processes, you can eventually get access to the data. But if you yourself know OEI community, there are not that many people who actually ever got access to data because it's very challenging process.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“To data, like the hospital holds your data, and the hospital decides whether they would give it to the researcher to work with this data or not.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“You did like, and you see in the days, and a significant amount, like right now in this country, there is no publicly available data set of modern mammographs that you can just go on your computer sign a document and get it. It just doesn't exist. I mean, obviously every hospital has its own collection of mammograms. There are data that came out of clinical trials. What we're talking about here as a computer scientist who just want to run his or her model and see how it works, this data like ImageNet doesn't exist. And there is called Florida data set, which is a film mammogram from 90s, which is totally not representative of the current developments, whatever you're landing on them doesn't scale up. This is the only resource that is available. And today there are many agencies that govern access.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“So, what machine learning can do here is utilize all this data to tell us Ellie who is likely to be susceptible and using all the information that is already there, be it imaging, be it your other tests. And, you know, eventually liquid biopsis and others, where the signal itself is not sufficiently strong for human eye to do good discrimination because the signal may be weak, but by combining many sources, machine which is trained on large volumes of data can really detect it earlier. And that's what we've seen with breast cancer and people are reporting it in other diseases as well.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“So for many cancers today, we really don't know what is your likelihood to get cancer. And for the vast majority of patients, especially on the younger patients, it really comes as a surprise. Like, for instance, for breast cancer, 80% of the patients are first in their families. It's like me. And I never thought that I had any increased risk because nobody had it in my family. And for some reason, in my head, it was kind of inherited disease But even if I would pay attention, the models that currently, these very simplistic statistical models that are currently used and in clinical practice, they really don't give you an answer, so you don't know. And the same true for pancreatic cancer, the same true for non-smoking cancer.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“As I got more into this field, I realized that cancer is of course terrible disease. The whole slew of terrible diseases out there, like neurodegenerative diseases and others. So we, of course, a lot of us are fixated on cancer just because it's so prevalent in our society and you see these people, but there are a lot of patients with neurodegenerative diseases and the kind of aging diseases that we still don't have a good solution for. And I felt as a computer scientist we kind of decided that it's other people's job to treat these diseases because it's like traditionally people in biology or in chemistry or MDs are the ones who are thinking about it. And after kind of start paying attention, I think that it's really a wrong assumption, and we all need to join the battle.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“Is crucial. For instance, the vast majority of pancreatic cancer patients are detected at the stage they are incurable. That's why they have such a Know terrible survival rate. It's like just a few percent over five years. It's pretty much today the sentence. But if you can discover this disease, Ellie, There are mechanisms to treat it, and in fact, I know a number of people who were diagnosed and saved just because they had food poisoning. They had terrible food poisoning. They went to Yar, they got scanned. There were early signs on the scan and that would save their lives. But this wasn't really an accidental case. So as we become better, we would be able to help to many more people that have likely to develop diseases. And I just want to say that”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“I cannot really assess it. What I do believe will happen with the advancement in machine learning is that a lot of types of cancer we will be able to predict way early and more effectively utilize existing treatments. I think, I hope at least, that with all the advancements in AI and drug discovery, we would be able to much faster find relevant molecules. What I'm not sure about is how long it will take the medical establishment and regulatory bodies to kind of catch up and to implement it. And I think this is a very big piece of puzzle that is currently not addressed.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“Know they may die, they already may have cancer, and they don't understand it. So you can really see how the mind changes that you can see that, you know, before that, you can ask, didn't you know that you're gonna die? Of course I knew, but it was kind of a theoretical notion. It wasn't something which was concrete. And at that point when you really see it and see how little means sometimes the system has to help them, you really feel that we need to take a lot of our brilliance that we have here at MIT and translate it into something useful.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“You're over sad and see it all. And people who are happier someday just because they feel better and for people who are in our normal realm, you take it totally for granted that you feel well that if you decide to go running, you can go running and you can, you know, you're pretty much free to do whatever you want with your body. I saw a community. My community became those people. And I remember one of my friends, Dina Katavi, took me to Prudential to buy me a gift for my birthday. And it was like the first time in months that I went to kind of to see other people. And I was like, wow. First of all, these people, you know, they're happy and they're laughing and they're very different from these other my people. And second thing, are they totally crazy? They're like laughing and wasting their money on some stupid gifts.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“Oh, absolutely, and it actually creates because, like, for instance, you know, there is parts of the treatment where you need to go to the hospital every day and you see, you know, the community of peoples that you see and many of them much worse than I was at a time.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“I look back into my years in science and I was thinking, you know, like 10 years ago, this was the biggest thing. I don't know, topic models. We have like millions of papers on topic models and variation on topics models. Now it's totally like irrelevant. You start looking at this, you know, what do you perceive as important at different point of time and how it fades over time. And since we have a limited time all of us have limited time on Earth, it's really important to prioritize things that really matter to you, maybe matter to you at that particular point, but it's important to take some time and understand what matters to you, which may not necessarily be the same as what matters to the rest of your scientific community and pursue that vision.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“And it's like the first time I've seen real life and real suffering. And I was thinking why are we trying to improve the parser or deal with some trivialities when we have capacity to really make change? And it was really challenging to me because on one hand, you know, I have my graduate students who really want to do their papers and their work and they want to continue to do what they were doing, which was great. And then it was me who really kind of re-evaluated what is the importance. And also at that point, because I had to take some break.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“But what I remember is that when I came back to MIT, I was kind of going the whole times through the treatment to MIT, but my brain was not really there. But when I came back really, I finished my treatment and I was here teaching and everything. I look back at what my group was doing, what other groups was doing, and I saw these trivialities. It's like people are building their careers on improving some parts around 2% or 3% or whatever. It's like, seriously, I did a work on how to decipher egoritic, like a language that nobody speak and whatever. Like, what is significance when I was suddenly, you know, I walked out of MIT, which is, you know, when people really do care, you know, what happened to your paper, what is your next publication to ACL, to the world where people, you know, people, you see a lot of sufferings. And I'm kind of totally shielded on it on daily basis.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“It would be really, I don't remember, you know, what was my thinking? It was really a mixture with many components at the time speaking in our terms. One thing that I remember, and you know, every test comes, and then you think, oh, it could be this, or it might not be this, and you're hopeful, and then you're desperate. So it's like there is a whole, you know, slow of emotions that goes through you.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“This is a great question, and I think that I was interviewed many times, and nobody actually asked me this question. I think 43 at a time. And the first time I realized in my life that I may die, and I never thought about it before. And there was a long time since you diagnosed until you actually know what you have and how CV is your disease. For me, it was like maybe two and a half months. I didn't know where I am during this time because I was getting different tests and one would say it's bad and I would say no, it is not. So until I knew where I am, I really was thinking about all these different possible outcomes.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“Capacity and the same way in computer science when we're doing recognition, when recommendation, many other areas, it's just probabilistic machinery process. And in some way, maybe in certain cases we shouldn't even attempt to understand or we can attempt to understand, but in parallel, we can actually do this kind of matchings that would help us to find QR or to do early diagnostics and so on. And I know that in these communities it's really important to understand, but I'm sometimes wondering what exactly does it mean to understand here?”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“And in traditionally, when people were thinking about marketing, they divided the population to different kind of subgroups, identify the features of this subgroup, and come up with a strategy which is specific to that subgroup. If you're looking about three recommendations, each time they're not claiming that they're understanding somebody, they're just managing from the patterns of your behavior to recommend your product. Now, if you look at the traditional biology, obviously I wouldn't say that I at any way educated in this field. But, you know, what I see that is really a lot of emphasis on mechanistic understanding. And it was very surprising to me coming from computer science how much emphasis is on this understanding. And given the complexity of the system, maybe the deterministic full understanding of these processes is beyond our”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“So this is a very interesting question. And if you're thinking as a computer scientist about this problem, I think one of the reasons that we succeeded in the areas we as a computer scientist succeeded is because we don't have, we are not trying to understand in some ways. Like if you're thinking about e-commerce, Amazon, Amazon doesn't really understand you and that's why it recommends you certain books or certain products, correct?”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“From Dana Farber, you know, how the experiments were done that, you know, there were some miscalculation, let's put it this way, and they tried it on the patients and those were children with leukemia and they died. And they tried another modification. You look at the process, how imperfect is this process. And, you know, like if we, again, looking back like 60 years ago, 70 years ago, you can kind of understand it. But some of the stories in this book, which were really shocking to me, were really happening maybe decades ago. And we still don't have a vehicle to do it much more fast and effective. And, you know, scientific the way I'm thinking computer science scientific.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“So it was actually centered on how people thought of curing cancer. For me, it was really a discovery how people, what was the science of chemistry behind drug development, that it actually grew up out of dying like coloring industry, that people who develop chemistry in 19th century in Germany and Britain to do the really new dice. They looked at the molecules and identified that they do certain things to cells. And from there, the process started. And, you know, like historically saying, yeah, this is fascinating that they managed to make the connection and look under the microscope and do all this discovery. But as you continue reading about it and you read about how chemotherapy drugs actually developed in Boston and some of them were developed and Farber, Dr. Farber.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“His well known fact that the reason the statistics in NLP took such a long time to become mainstream because there were quite a number of personalities which didn't believe in this idea and didn't stop research progress in these areas. So I do not think that kind of asymptotically maybe personalities matters, but I think locally it does make quite a bit of impact.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“Not necessarily that they are more important than ideas, but I think that ideas on their own are not sufficient. And many times, at least at the local horizon, it's the personalities and their devotion to their ideas is really that locally changes the landscape. Now, if you're looking at AI, like let's say 30 years ago, dark ages of AI or whatever, what the symbolic times you can use any word, you know, there were some people. Now we are looking at a lot of that work and we are kind of thinking this was not really maybe a relevant work. But you can see that some people managed to take it and to make it so shiny and dominate the academic world and make it to be the standard. If you look at the area of natural language processing”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“To LA, to a conference, and they ask somebody in the airport how to find a cab or something. And then I noticed that this person is talking in a very strange way. And my first thought was that this person have some, you know, pronunciation issues or something. And I'm trying to talk very slowly to him. And I was with another professor, Ernst Frankl. And he's like laughing because it's funny that I don't get that the guy is talking in this way because he thinks that I cannot speak. So it was really kind of mirroring experience and it led me think a lot about my own experiences moving from different countries. So I think that books play a big role in my understanding of the world.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“This is not my case. And then she notices that the person who talks to her, you know, talks to her in a very funny way, in a very slow way. And she's thinking that this woman is disabled. And she's also trying to kind of accommodate her. And then after a while, when she finishes her discussion with this officer from her college, Sees how she interacts with the other students, with American students, and she discovers that actually And he thought, wow, this is a funny experience. And literally within a few weeks, I went.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“And this is a book about a young female student who comes from Africa to study in the United States and it describes Help us in her studies and her life transformation that in a new country and kind of adaptation to a new culture. And when I read this book, I saw myself in many different points of it. But it also kind of gave me the lens on different events and some events that I never actually paid attention, one of the funny stories in this book is how she arrives to her new college and she starts speaking in English and she has this beautiful British accent because that's how she was educated in her country.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“That book, despite the fact that I am in the business of science, really opened my eyes on how imprecise and imperfect the discovery process is and how imperfect our current solutions and what makes science succeed and be implemented and sometimes it's actually not the strengths of the idea but devotion of the person who wants to see it implemented. So this is one of the books that, you know, at least for the last year quite changed the way I'm thinking about scientific process just from the historical perspective and what do I need to do to make my ideas really implemented Let me give you an example of a book which is not kind of which is a fiction book A book called Americana”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source
“I think because I'm spending a lot of my time at MIT and previously in other institutions where I was a student, I have a limited ability to interact with people. So a lot of what I know about the world actually comes from books. And there were quite a number of books that had profound impact on me and how I view the world. Let me just give you one example of such a book. Maybe a year ago read a book called The Emperor of All Melodies. It's a book about it's kind of a history of science book on how the treatments and drugs for cancer were developed.”
2019-09-23 · Lex Fridman Podcast · Regina Barzilay: Deep Learning for Cancer Diagnosis and Treatment · IDENTIFIED FROM THE TRANSCRIPT · source