Must-haves for machine learning to thrive in healthcare

When John Guttag keynotes the HIMSS and Healthcare IT News Big Data and Healthcare Analytics Forum in Boston on October 24, the MIT professor will describe the unique challenges of applying machine learning to healthcare – as well as the huge potential for efficiencies and quality improvements as these data techniques become more widespread across the industry. Guttag, who heads the Data Driven Inference Group at the MIT's Computer Science and Artificial Intelligence Laboratory, and his MIT students are currently working closely with Mass General on integrating machine learning into clinical workflows, specifically with the aim of reducing healthcare-associated infections. "I want to actually see things change in the system, not just write papers saying things could change," Guttag said. "The goal here is to have something good happen. I hope a year from now I'm able to say, 'Guess what, we've lowered the rate of nosocomial infections at MGH – and more importantly put together a description of how we've done it that is exportable to other organizations.'"