An online contest for data scientists has produced a great leap forward in efforts to predict when someone with epilepsy is going to have a seizure. The winning team used data on electrical activity in the brain to develop an algorithm that predicted seizures 82 percent of the time.
That "blew the top off" previous efforts, says Brian Litt, a professor of neurology and bioengineering at the University of Pennsylvania who helped oversee the competition. In the past, he says, researchers have struggled to find an algorithm that did better than chance.
"This has real clinical potential," says Walter Koroshetz, acting director of the National Institute of Neurological Disorders and Stroke, a sponsor of the contest. "We'd like to develop therapies that come in when they are needed instead of people taking medicine all the time."
Epilepsy, which is often compared to an electrical storm in the brain, affects nearly 1 percent of people worldwide. The most common treatment is medication, which can leave people feeling tired or dizzy. Other options include surgery and a new type of implanted device that uses electrical pulses to prevent seizures.
[For more of this story, written by Jon Hamilton, go to http://www.npr.org/blogs/healt...t-epileptic-seizures]
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