Faster medical treatment saves lives. Machine Learning is already saving lives, by scouring a multitude of patients’ data and comparing them to one patient’s health data to detect symptoms 12 to 24 hours sooner than a doctor could. “In many pressing medical problems, the answers to knowing whom to treat, when to treat, and what to treat with, might already be in your data” says Suchi Saria. Learn how TREWS (Targeted Real-time Early Warning Score) is leading the way to save lives.
Suchi Saria is a professor of computer science and health policy, and director of the Machine Learning and Health Lab at Johns Hopkins University. Her research is focused on designing data solutions for providing individualized care.