Speaker "Jonathan Rubin" Details Back



Deep Learning in Healthcare


This talk will provide an overview of deep learning models we have developed for a range of medical applications. We present examples of algorithms that automatically processes and analyze: 1. Electronic health records to predict life threatening events in the intensive care unit, 2. Physiological waveforms, such as the electrocardiogram, to detect abnormalities in heart rhythms, and 3. 3D medical images for semantic segmentation of brain lesions. We explore a range of deep learning models that have been successful in other domains and show how they can be adapted to medical applications.
Who is this presentation for?
AI Researchers, healthcare professionals, healthcare industry
Prerequisite knowledge:
What you'll learn?
Deep learning approaches applied to healthcare data and applications


Jonathan Rubin is a Senior Scientist at Philips Research North America and a Research Affiliate at MIT CSAIL. Previously, he was a researcher in the System Sciences Laboratory at Palo Alto Research Center (Xerox PARC). Jonathan received his PhD in Computer Science in 2013 specializing in Artificial Intelligence. His current research focuses on the development and application of machine/deep learning algorithms that analyze healthcare data, including physiological waveforms and biomedical imaging data.