Want to know what software-driven health care looks like? This class offers some clues.

MIT professors David Sontag and Peter Szolovits don’t assign a textbook for their class, 6.S897HST.956 (Machine Learning for Healthcare), because there isn’t one. Instead, students read scientific papers, solve problem sets based on current topics like opioid addiction and infant mortality, and meet the doctors and engineers paving the way for a more data-driven approach to health care. Jointly offered by MIT’s Department of Electrical Engineering and Computer Science (EECS) and the Harvard-MIT program in Health Sciences Technology, the class is one of just a handful offered across the country. “Because it’s a new field, what we teach will help shape how AI is used to diagnose and treat patients,” says Irene Chen, an EECS graduate student who helped design and teach the course. “We tried to give students the freedom to be creative and explore the many ways machine learning is being applied to health care.” Two-thirds of the syllabus this spring was new. Students were introduced to the latest Continue reading Want to know what software-driven health care looks like? This class offers some clues.