Detecting consumer decisions within messy data

Tuesday, December 22, 2015 - 00:22 in Mathematics & Economics

Millions of people each month report positive and negative health care feedback across the Web. Some jump into forums to complain about ineffective prescriptions or to discuss which drugs are best to treat illnesses. Others take to blogs to describe symptoms and how to get relief. MIT spinout dMetrics believes this online chatter is an information treasure-trove for the health care industry. “In health care, there’s this gigantic world of unstructured data that needs to be translated into useable information,” says Paul Nemirovsky PhD ’06, who co-founded dMetrics with Ariadna Quattoni PhD ’09. The startup has developed a platform called DecisionEngine that uses machine learning and natural language processing — which helps computers better understand human speech — to mine billions of conversations about drugs, medical devices, and other health care products. These discussions are happening on blogs, Facebook, Twitter, forums, and even in comments accompanying news articles and videos. From those vast...

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