Healthcare Technology Featured Article

April 05, 2013

Healthcare Supercomputer Apps Win Big

The classic phrase, “An Apple A Day Keeps the Doctor Away” could soon be abbreviated to “An App A Day Keeps The Doctor Away.”   

The top three winners in a $100,000 graph analytics contest held by YarcData (a unit of the supercomputing firm, Clay) all showcased work that seeks to advance medical science.

Recipient of the first prize, a lump of $70,000, was a team from the Seattle-based Institute for Systems Biology, who matched unstructured data from medical journals with structured data from genomic and proteomic registries to gain insight into thousands of cancer patients. The team used YarcData's uRIKA graph appliance to comprehend how cancer interferes with biological networks.

The technology also enabled them to identify drugs that, though traditionally used for other conditions, may be able to help fight certain cancers.

Dr. Bruce Hendrickson, senior manager for computational sciences and mathematics at Sandia National Laboratories in New Mexico, was a contest judge who was highly impressed by the first prize winning work.

“The winning entry demonstrated classic features of big data problems: a large volume of complex information from a variety of disparate sources and a need to manage data input and output at a high velocity. The team's submission exemplified the power of graph analytics for gaining insight into difficult knowledge-discovery problems,” he said.

Second place went to a research team from the University of California at Santa Barbara, which seeks to find answers pertaining to autism. The group probed clusters of disease precursors in search for clues that could illuminate the still mysterious condition.

Taking third was Dr. Abraham Flaxman, an assistant professor at the University of Washington's Institute for Health Metrics and Evaluation. He developed a computer model that can predict patient risk and mortality in the 30 days following a heart attack.

In response to his third-place win, Flaxman – a mathematician by training – was humble; “I'm not here to tell you I've solved the problem of predicting 30-day mortality [for individual patients],” he said. “This is where computer scientists have been overpromising for years.”

Edited by Braden Becker

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