Researchers from IBM and the University of Melbourne have developed a proof-of-concept seizure forecasting system that predicted an average of 69 percent of seizures across 10 epilepsy patients in a dataset. The system, which the scientists claim is "fully automated, patient-specific, and tunable to an individual's needs", uses a combination of deep-learning algorithms and a low-power "brain-inspired" computing chip to predict when seizures might occur, even if patients have no previous prediction indicators. IBM noted that a one-size-fits-all approach is inadequate when it comes to epilepsy management, as the condition manifests itself uniquely in each patient. "Epilepsy is a very unique condition where triggers for seizures are specific to individual patients -- some may be sensitive to heat, others to stress. This is why deep learning is important because it can interpret the data and look for signs and patterns specific to an individual's brain signals," an IBM spokesperson told ZDNet.
Dec-6-2017, 03:00:04 GMT