Artificial intelligence algorithms are everywhere in healthcare. They sort through patients’ data to predict who will develop medical conditions like heart disease or diabetes, they help doctors figure out which people in an emergency room are the sickest, and they screen medical images to find evidence of diseases. But even as AI algorithms become more important to medicine, they’re often invisible to people receiving care.
Artificial intelligence tools are complicated computer programs that suck in vast amounts of data, search for patterns or trajectories, and make a prediction or recommendation to help guide a decision. Sometimes, the way algorithms process all of the information they’re taking in is a black box — inscrutable even to the people who designed the program. But even if a program isn’t a black box, the math can be so complex that it’s difficult for anyone who isn’t a data scientist to understand exactly what’s going on inside of it.
Patients don’t need to understand these algorithms at a data-scientist level, but it’s still useful for people to have a general idea of how AI-based healthcare tools work, says Suresh Balu, program director at the Duke Institute for Health Innovation. That way, they can understand their limitations and ask questions about how they’re being used.
Some patients can get a little jumpy when they hear algorithms are being used in their care, says Mark Sendak, a data scientist at the Duke Institute for Health Innovation. “People get really scared and nervous, and feel threatened by the algorithms,” he says.
Those patients can be nervous about how hospitals are using their data or concerned that their medical care is being directed by computers instead of their doctors. Understanding how algorithms work — and don’t work — may help alleviate those concerns. Right now, healthcare algorithms have very narrow uses: a computer program isn’t going to make major medical decisions, but it might help a doctor decide whether a set of medical scans needs closer scrutiny.
To help demystify the AI tools used in medicine today, we’re going to break down the components of one specific algorithm and see how it works. We picked an algorithm that flags patients in the early stages of sepsis — a life-threatening complication from an infection that results in widespread inflammation through the body. It can be hard for doctors to identify sepsis because the signs are subtle, especially early on, so it’s a common target for artificial intelligence-based tools. This particular program also uses mathematical techniques, like neural networks, that are typical of medical algorithms.
The algorithm we’re looking at underpins a program called Sepsis Watch, which Sendak and Balu helped develop at Duke University. Sepsis Watch went online in 2018 after around three years of development. Today, when someone is hospitalized at a Duke hospital, the program could be keeping an eye on them.
Here’s what it’d be doing.