Explore a 59-minute conference talk on time series machine learning for healthcare deployment, presented by Anna Goldenberg at the EWSC-MIT EECS Joint Colloquium Series. Delve into the application of ML in healthcare settings, including ICU environments and pediatric hospitals. Learn about explainability tools, feature importance, evaluation methods, and representation challenges in medical AI. Discover innovative approaches like HDP Flow States and the Lifeline pipeline for real-time evaluation. Gain insights into model transferability, feature selection, and the use of intervention and continuous data in healthcare ML. Engage with the pressing biomedical questions and foundational machine learning advances discussed in this collaborative series between the Eric and Wendy Schmidt Center at the Broad Institute and AI+D within MIT's EECS Department.
Time Series Machine Learning for Deployment in Healthcare