IBM and JDRF are partnering to develop and apply machine learning techniques to the analysis of Type 1 diabetes data. The pair aims to identify risk factors that cause the onset of the disease in children.
IBM scientists still use machine learning algorithms to analyze at least three datasets, according to a statement. Specifically, they are looking to pinpoint patterns that could lead to new ways of preventing or delaying Type 1 diabetes in children. Using previously collected data from global research projects, they will create a “foundational set of features” that is common to all of the data sets.
“The models that will be produced will quantify the risk for T1D from the combined data set using this foundational set of features,” IBM said in the statement.
JDRF is a leading funder of Type 1 diabetes research. Teaming up with IBM could unlock trends in the data that were previously indiscernible. In 2016, IBM Watson partnered with the American Diabetes Association to apply cognitive computing to research and clinical data.
“JDRF supports researchers all over the world, but never before have we been able to analyze their data comprehensively, in a way that can tell us why some children who are at risk get T1D and others do not,” said Derek Rapp, JDRF CEO, in the statement.
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“Nearly 40,000 new cases of type 1 diabetes will be diagnosed in the U.S. this year. And each new patient creates new records and new data points that, if leveraged, could provide additional understanding of the disease,” said Jianying Hu, senior manager and program director at the Center for Computational Health at IBM Research. “The deep expertise our team has in artificial intelligence applied to healthcare data makes us uniquely positioned to help JDRF unlock the insights hidden in this massive data set and advance the field of precision medicine toward the prevention and management of diabetes.”
Earlier this year, JDRF set up a $42 million fund with a goal of raising up to $80 million. The fund is managed separately from JDRF and is particularly interested in companies working on “artificial pancreas” technology, metabolic control, encapsulation and replacement, and prevention and restoration therapies.