3 Questions: Carlo Ratti on big data and health predictions
What can big data tell us about the predictability of medical conditions? A new study by MIT researchers published in the journal Scientific Reports digs into this question by looking at anonymous data from over 500,000 patients. Among the findings is that for 43 percent of the patients, the data can help predict which of 1,719 subcategories of diseases are most likely to occur next. The co-authors of the paper are Carlo Ratti, director of MIT’s Senseable City Laboratory, and two former computer science researchers at the lab, Dominik Dahlem (who is the lead author) and Diego Maniloff. The data originated with General Electric, which collaborated with Senseable City on a 2011 project on visually plotting health care data. MIT News spoke with Ratti about the new study. Q. What is your central finding in the new study? A. The results are quite interesting: This is one of the first analyses of...