We use machine learning and computer vision to improve outcomes in medicine, finance, and sports
Our group focuses on the application of advanced computational techniques to medicine. Current projects include prediction of adverse medical events, prediction of response to therapies, non-invasive monitoring and diagnostic tools, and tele-medicine.
We aim to study the causes and transmission modes of infectious diseases among members of a community in the presence of hidden, asymptomatic spreaders of the pathogen.
Transitioning machine learning models across electronic health record (EHR) versions can be improved by mapping different EHR encodings to a common vocabulary.
We aim to utilize supervised machine learning techniques on player tracking data from the game of basketball to automatically discover relationships between player movement and offensive success.
Developed at MIT’s Computer Science and Artificial Intelligence Laboratory, new system uses a patient's ECG signal to estimate potential for cardiovascular death
