Monday, January 26, 2015

Big Data and iConquerMS

So what is meant by ‘Big Data’ in medical research?
I asked Dr. Ken Buetow, the iConquerMS™ project team’s informatics expert from Arizona State University and former director of the National Cancer Institute’s Center for Biomedical Informatics and Information Technology, to explain.

“Big Data in biomedicine refers to large quantities of diverse types of data — clinical care encounters, demographic, geographic, individual clinical experiences, lifestyle, personal preferences, and molecular characterizations from tens of thousands of individuals. With Big Data, one has the possibility of discerning patterns and associations that would be undetectable through traditional approaches,” according to Buetow. “I’m reminded of the Michaelangelo quote that ‘every block of stone has a statute inside it, and it is the task of the sculptor to discover it.’ One might say all Big Data contains insights and it’s the job of the data scientist to find them!”

Big Data has the capacity to turn anecdote into evidence.
The more information that is shared, the better equipped researchers will be to discover patterns associated with smaller, more specific, segments of the MS population. With more data points, our multitude of individual anecdotes and experiences become a pointillistic tapestry of evidence which can begin to answer more interesting questions about the disease and its treatment.

How does it work?
“By embracing the Big Data paradigm, iConquerMS™ enables research that complements traditional approaches,” says Buetow. “iConquerMS™ collects large volumes of diverse data from all who are interested in sharing information. Questions are then asked against the collected data. These questions can come from both the research community and iConquerMS™ participants. Instead of conducting a new research study for each question – contacting new individuals and collecting new data – the data previously shared can be queried and evaluated.”

Read this post in its entirety:
iConquerMS Uses Big Data Approach to MS Research

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