As big data grows, the need for AI comes into focus

June 20, 2015 in Medical Technology

No one questions that the era of big data is here, but Dr. Anthony Chang warns that the deluge of medical information is just beginning.

[See also: AI, robotics, biosensors 'exploding onto the scene,' set to transform care]

“By 2020, there will be 200 times more data than any physician can absorb,” said Chang, a practicing pediatric cardiologist. “And its doubling every two years.”

In his keynote address at the National Healthcare Innovation Summit in Chicago Wednesday morning, Chang said he worries that lives are being lost from the unrealized opportunity.

[See also: Watson has big plans for the future]

“There is nothing worse than when a child is lost because we don’t have access to the right knowledge,” he said.

The longterm solution Chang is working toward is “Intelligence-as-a-Service,” a network that could make it possible for doctors to tap into knowledge from specialists anywhere when they encounter a medical situation that is not responding to treatment.

“Why can’t we get access to that intelligence?” he asked.

Today, one of the problems is that the data being collected is unstructured; Chang estimates that about 90 percent of healthcare data being collected is not in a structured format. Until entities like IBM Watson came along, most of the bio- data being collected can’t be integrated with data in existing analytic systems.

“And in the future there will be tsunamis of data – particularly genomic data and yet another layer of behavioral data produced by wearables,” he said. “And with all that data, there’s very little intelligence coming our way. “

The future will require a different approach, in which data is used in a BioIntelligence framework similar to deep learning, said Chang. Multiple layers of analytics are used to extract value from data.

He cited the work being done by Excel Medical Electronics with the BedMasterEx data acquisition solution working with IBM’ Watson’s InfoSphere Streams technology. He described the solution as four-stage architecture in which data is acquired in a SQL format, moves to an adaptation layer, then to an analytical layer and finally a delivery layer using HTTP. InfoSphere Streams is a sensory interface for Watson, making it possible for unstructured bio  data to be analyzed.

Chang then introduced Robert Merkel, vice president of client engagement at IBM Watson Health, who described Watson as a “cognitive system” which is taught, not programmed. It can learn, and improve its performance based on its experiences and it can work with sensory and non-traditional data.

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