Andrew Work speaks to Li Yingrui, co-founder and chief scientist of iCarbonX, at the Emtech Hong Kong Event hosted by MIT Technology Review and Koelnmesse. iCarbonX aims to build an ecosystem of digital life based on a combination of an individual’s biological, behavioral and psychological data, the Internet and artificial intelligence.
NEXCHANGE: I’m Andrew Work with NexChange and we are down at the EmTech Hong Kong event. This is the MIT Technology Review event here in Hong Kong. And MIT that means that they’ve brought together some of the smartest people in the world that are doing really cutting-edge work looking at the future.
I’m here talking to the young guy who is the co-founder and chief scientist for iCarbonX and he gave an absolutely fantastic, really mind-blowing presentation early today about the future of healthcare. And if correct me if I’m wrong, but the way that I took what you’re talking about is that there’s all this data out there how people think about different parts of their health and how it affects them over different periods of life. So people might think I’ve gotten a probiotic yogurt to manage my personal biome, the bacteria in my gut on a day-to-day basis or they might say maybe I should get tested for a gene that might lead me to having breast cancer in the future. It’s kind of a lifetime decision but that’s a lot of data people deal with that in a very chaotic fashion moment to moment in their head but no company or healthcare companies ever put that together. So that they can really predict what’s going to happen with people. How are you going to address that?
LI YINGRUI: So this is what I can say about the propositioning, so we want to play as data platform to serve as a data layer underneath all these different type of health care industry, to really build up a human centric profile for each of our customer. And then that in each of a scenario that people would like to enjoy some type of health care health care service, no matter its yogurt or it’s some type of medical testing, so that at that decision as a decision point, we would like to integrate all the unit together to make others a whole picture decision rather than a specific local decision simply based on that particular demand. So that’s what we would like to do and and we hope that with the technology we are having both the Baltic side as well as on the data technology side, we hope that our expertise on the cross-disciplinary science and technology could help us to leverage and to play as a neutral role in all of this healthcare industry. So that we can add value to their original service and in exchange we can get access to the data and we can cross scenario to streamline all the data together to make our service actually human centric. So that’s what we’re looking for.
NEXCHANGE: Okay, this is really interesting. You taking genomics and you’re taking artificial intelligence and deep learning combining it all to get this broad holistic picture.
LI YINGRUI: Or dynamic profile as well, proteins change it day by day so so we also take care of those type of data. And also we talk about mobile health care stuff. Your step counter maybe it has continued a EEG ECG recorders all type of things. We put all these different types of data together so they are all integrating together to make some good sense of how your health actually goes.
NEXCHANGE: I mean that was really interesting. Your presentation that you talked about the fact that it’s not a static situation where you walk in here’s how you are now and therefore we’re going to treat you. You’re getting continuous flow of information and then providing feedback to have predictive power. Can you tell us why that’s so important how healthcare companies are going to use that?
LI YINGRUI: Let me put it in two sides. An example would be currently people believe that you have hypertension when your blood pressure is over 120 and 80 but just put a very simple imagination. So if one he has this 120 and 80 when he was at age of 18 and now is 20 years after he is still like 120 and 80. It’s pretty much stable thing. He’s not really threatened but if one is originally has a relatively lower blood pressure like 90-60 and now he’s a hundred something like that. That means although that he’s not at the cause of a clinical threshold for this time. But if you look at the trend line of his life, that means something really serious is happening to his life, so the first first thing is we need to think about that health is something that you need to manage and it’s a trend line of your own life. So you need to get multiple points during a life profile so that you can actually draw your own picture and it’s no one else actually but you can know.
And secondly back to the feedback thing is because now we have to integrate multiple on domains knowledge together. That’s including a medical domain including nutrition domain including sporting exercise domain so sometimes you need a one centralized algorithm or a centralized system. They adequately make decisions by aggregating all those have expertise together and this is what we typically call fear intelligence. But the key thing works for intelligence is they need to keep on learning from whom. One is learning from different experts. Another one most important is the action learning from the user’s feedback so if you say this is nice. I really got into a good status. Now that is a positive price. Let’s get a score right. And you don’t feel good about the treatment. That type of negative feedback also gives back to the system and to make it also smarter. You learn from those bad practices.
NEXCHANGE: So the artificial intelligence isn’t just learning because it’s been programmed by experts. You understand health but it is actually learning based on the data that it is receiving on a continuous basis.
LI YINGRUI: Yes, in the future it’s actually all those users feedback actually helps most in an artificial intelligence system if we want to do a smart healthcare management.
NEXCHANGE: This is really exciting stuff about how all these different technologies are coming together. I hope the computing world can keep up with you.