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. 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. 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. 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. The algorithm we're looking at underpins a program called Sepsis Watch, which Sendak and Balu helped develop at Duke University.

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.