Brittany Wenger – TRANSCRIPT
Be ready to pick your jaw back up as we welcome 17-year-old Brittany to the TEDxAtlanta stage. All-right. So. Ok. That’s loud. I want you all to picture a little kid in the “why” phase. You know that kid that’s always asking questions. “Why is the sky blue?” “Why is the glass green?”
And about million other questions per day. Now imagine, hypothetically speaking of course, what it would be like 15 years down the line if that kid was still in a “why” phase. As you may have imagined this isn’t quite a hypothetical situation. I am a 17-year-old who loves to ask questions.
But, it wasn’t until I found science that I found my answers and more questions because with science the more you know the more you wonder. It’s an infinite process. One which I am completely enamored by. So, I love science because it gives us the opportunity to revolutionize the world around us. I think I first started seeing how many implications science really has where I was little.
My brother was born premature and he spent over 60 days in a hospital his first year and many times after that we would go back and visit. I really grew to idolize men and women in scrubs because I could see that they were saving lives and using science to have a positive impact on the world. Then as a 7th-grader my passion for science grew even further. I was taking an elective on futuristic thinking. Quite by accident I stumbled across artificial intelligence. I was enthralled for computers can do things that humans can’t. That just is mind-boggling. I went home, I bought a coding book, and I decided that that’s what I was going to focus on.
Now, this was pretty naive. I never actually coded anything. So I started with all the stereotypical beginner programs. Hello-world, card games, et cetera. And, eventually I did program artificial intelligence and it played soccer because at that time and still today I was a very avid soccer player.
Now my passions have surpassed my grade school aspirations. I’m combining medical research and computer science to improve breast cancer diagnostics. And I did this so that my computer program could answer one simple question. Is a breast mass malignant or benign? And this is really important because fine needle aspirates, the least invasive form of biopsy, are actually the least conclusive. This is a big problem because a lot of doctors can’t use them. If they can be used it would lead to earlier detection, less invasion and less cost.
So, I tried to create a tool for doctors to use so that they could diagnose these fine needle aspirates. And I did this by creating an artificial neural network which is a type of program that can actually detect patterns that humans can’t detect. I, then, put my artificial neural network that was diagnosing fine needle aspirates in a cloud because the cloud is this amazing elastic entity. They can scale to support usage by every hospital in the world. The current network is working really well. It is 99.1% sensitive to malignancy. And this is huge because this is the number that could save a lot of lives and can make the program hospital ready.
In addition, I’ve run 7.6 million tests and I’ve proven that as I get more data the success rate should increase while the inconclusivity rate should decrease. So, why is this important? One in eight women is impacted with breast cancer. And, these statistics are just startling. And, unfortunately, they are on the rise. However, when you have a personal encounter with a breast cancer that’s when the statistics become more of a reality. For me, that happened in my sophomore year of high school.
My cousin was diagnosed with breast cancer. And, I saw the pain that it inflicted on her and the rest of the family. I was inspired to make a difference. And my way of making a difference was to try to improve breast cancer diagnostics. So, I talked to you a little bit about fine needle aspirates. You know that they are the least invasive procedure. You know they are also the least conclusive. So, specifically in the United States, they are very rarely used. Most doctors won’t use them.
What they actually do is they cause the patients about the level of discomfort of a blood test. A doctor sticks a fine needle into a palpable breast mass, and a few cells are extracted and then stained, and then, doctors look at them under a microscope. And then, traditionally doctors would decide whether the breast mass is malignant or benign. Now these are great tests because they are the most accessible to the general public, so they can lead to earlier detection. They are also about 4 times cheaper than the core biopsy, which is the current means of diagnosing aspirates. In addition, they cause women less physical and emotional scars, which is huge when you have to go through something as big as breast cancer. So that was the biology side of the project.
But what’s great about science right now is a lot of the breakthroughs are coming through interdisciplinary research. So here is a little bit on the computer side of the project. Artificial neural networks are actually programs that can model the brain’s neurons and innerconnectance to detect patterns that we can’t. And, this give them infinite potential because they are not limited on what we know and for something like cancer they are especially applicable because cancer is constantly mutating and constantly transforming.
Neural networks are constantly learning so they can pick up on these changes learn how to handle them, and still diagnose the masses correctly which gives them a lot of potential. And not only are neural networks being used in medical realm, but they’ve got a lot of exciting applications.
Currently they are being used at CERN where the Higgs Boson discoveries continue. They are also being used in more common place things such as your iTunes and Netflix all the suggestions are based on your prior experiences and they have neural networks figuring out what they think you’ll like. Future implications could lead to smarter rovers and a video game that just got smarter as a player got smarter. So it lasted forever. Or even advances in earthquake detection.
The other part of the computer science behind this project is the cloud. And a lot of us have probably heard about the cloud. It’s this huge technology buzz term right now. And what cloud allows for is that allows for servers to host my project. So what I mean by that is right now I am the only one and a few other hospitals are accessing my program. So we don’t use that much server space. But tomorrow if a million hospitals decide they are interested in using it at the same exact time, my program will expand to all these different servers and I will be able to accommodate that. So I built it as a cloud service. And what that means is essentially my program exists out in cyberspace. And it’s just waiting for somebody to use it.
So it’s looking for these messages and right now you can call my program via a web application. So you can go online to Cloud4Cancer.appspot.com. Doctors can use it. It’s working great. However in order for a tool to be reliable and the whole purpose of this is to provide a tool for doctors it needs to be accessible. So some doctors are still using old PC systems. Others have moved towards mobile tablets. And there are new technologies that will emerge in the future. I can code platforms for these specific technologies. And they will be able to call my app and it will run. And one of the working examples of this is I am actually working with an institute in Italy. They were able to create a program to reclassify the samples they already have based on my program’s inputs, and then call my service and get a response. You might be wondering at this point how the neural network actually works and how it applies to breast cancer.