TR10: Personalized Medical Monitors
John Guttag says using computers to automate some diagnostics could make medicine more personal.
This article is one in a series of 10 stories we're running this week covering today's most significant emerging technologies. It's part of our annual "10 Emerging Technologies" report, which appears in the March/April print issue of Technology Review.
In late spring 2000, John Guttag came home from surgery. It had been a simple procedure to repair a torn ligament in his knee, and he had no plans to revisit the hospital anytime soon. But that same day his son, then a junior in high school, complained of chest pains. Guttag's wife promptly got back in the car and returned to the hospital, where their son was diagnosed with a collapsed lung and immediately admitted. Over the next year, Guttag and his wife spent weeks at a time in and out of the hospital with their son, who underwent multiple surgeries and treatments for a series of recurrences.
During that time, Guttag witnessed what became a familiar scenario. "The doctors would come in, take a stethoscope, listen to his lungs, and make a pronouncement like 'He's 10 percent better than yesterday,' and I wanted to say, 'I don't believe that,'" he says. "You can't possibly sit there and listen with your ears and tell me you can hear a 10 percent difference. Surely there's a way to do this more precisely."
It was an observation that any concerned parent might make, but for Guttag, who was then head of MIT's Department of Electrical Engineering and Computer Science, it was a personal challenge. "Health care just seemed like an area that was tremendously in need of our expertise," he says.
The ripest challenge, Guttag says, is analyzing the huge amounts of data generated by medical tests. Today's physicians are bombarded with physiological information--temperature and blood pressure readings, MRI scans, electrocardiogram (EKG) readouts, and x-rays, to name a few. Wading through a single patient's record to determine signs of, say, a heart attack or stroke can be difficult and time consuming. Guttag believes computers can help doctors efficiently interpret these ever-growing masses of data. By quickly perceiving patterns that might otherwise be buried, he says, software may provide the key to more precise and personalized medicine. "People aren't good at spotting trends unless they're very obvious," says Guttag. "It dawned on me that doctors were doing things that a computer could do better."
For instance, making sense of the body's electrical signals seemed, to Guttag, to be a natural fit for computer science. Some of his earlier work on computer networks caught the attention of physicians at Children's Hospital Boston. The doctors and the engineer set out to improve the detection of epileptic seizures; ultimately, Guttag and graduate student Ali Shoeb designed personalized seizure detectors. In 2004, the team examined recordings of the brain waves of more than 30 children with epilepsy, before, during, and after seizures. They used the data to train a "classification algorithm" to distinguish between seizure and nonseizure waveforms. With the help of the algorithm, the researchers identified seizure patterns specific to each patient.