Better Medicine Through Machine Learning: Suchi Saria (Transcript)

Full Text of Machine Learning Expert Suchi Saria’s talk titled “Better Medicine through Machine Learning” at TEDxBoston conference.

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TRANSCRIPT:

Suchi Saria – Associate Professor of Machine Learning and Healthcare at Johns Hopkins University

Let me introduce you to Mrs. Manny. She came to the emergency room. She is fifty two years old. She came to the emergency room with a foot sore. Doctors investigated her foot sore and she ended up staying there in the hospital for 22 days.

Here’s what happened.

When she came to the emergency room for a foot sore, they inspected her, they saw no real reason for medical concern but they wanted to monitor in case her foot sore was infected. So, they put her in the general ward.

On day three, she starts developing symptoms of what looks like mild pneumonia. They give her the usual treatment of antibiotics and all’s good but then her condition starts to worsen.

On day six, she develops what’s called ‘tachycardia’ that means in medical speak, her heart rhythm has accelerated dramatically. She then has trouble breathing.

On day seven, she experiences septic shock; that means her body is in crisis. Incidentally, mortality in shock is one in two. Now, it’s only at this point that the doctors get really concerned and they transfer her to the intensive care unit.

ICUs are the units where the most critically ill patients get cared for. Here, they give her every possible treatment to stabilize her but her condition only worsens.

First, her kidneys start to fail. Then her lungs fail and on day 22, she dies.

Mrs. Manny did receive the right set of treatments. The problem is, she received them only too late. What Mrs. Manny experienced was an infection that turned into sepsis.

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Let me tell you a little bit about what sepsis is. Sepsis occurs when infection releases chemicals in your blood to tackle the infection. So, your body releases chemicals to fight the infection. Now, this chemical can trigger a negative inflammatory response. When this inflammation triggers this negative inflammatory response, what it can then do is cause a cascade of changes, leading your organs to fail, leading to death.

Sepsis is the 11th leading cause of death, more than breast cancer and prostate cancer combined. Turns out, sepsis is preventable if treated early, okay?

So, then what’s the catch? Doctors find it very hard to recognize sepsis. In fact, a Harvard study shows with 93 leading academic experts that when they were given several cases of patients with and without sepsis, they couldn’t agree.

Two years ago, my nephew, he was admitted to the best Hospital in India and he died of sepsis. My family was devastated.

I’m a machine learning expert and what I do is study ways in which we can use large messy datasets to enable intelligent decision-making. So, natural question for me was, could machine learning have helped? Could machine learning have helped Mrs. Manny and my nephew?

So, this led to a massive effort with my colleagues at Hopkins to design what we call ‘the targeted real-time early warning system’ or TREWS based on machine learning. I’ll give you a sneak peek into what TREWS is and how we’re using it to tackle sepsis.

Let me take a step back and tell you a little bit about what machine learning is and what’s AI.

Artificial intelligence is a field of study where we teach computers how to learn. Okay? Just like you teach your kids. Machine learning is one way of doing this, by designing code or programs that teach computers stuff over time by interacting with the environment or watching. Okay?

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So, I’m going to show you a video of some robots learning how to walk. I find it funny how it shudders. So, you’re probably now thinking this is hopeless.

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