Quantifying Clinical Outcome Measures in Patients with Epilepsy Using the Electronic Health Record

no code implementations • BioNLP (ACL) 2022 • Kevin Xie, Brian Litt, Dan Roth, Colin A. Ellis

A wealth of important clinical information lies untouched in the Electronic Health Record, often in the form of unstructured textual documents.

Text Summarization

RAMSES: A full-stack application for detecting seizures and reducing data during continuous EEG monitoring

no code implementations • 3 Sep 2020 • John M. Bernabei, Olaoluwa Owoputi, Shyon D. Small, Nathaniel T. Nyema, Elom Dumenyo, Joongwon Kim, Steven N. Baldassano, Christopher Painter, Erin C. Conrad, Taneeta M. Ganguly, Ramani Balu, Kathryn A. Davis, Jay Pathmanathan, Brian Litt

Objective: Continuous EEG (cEEG) monitoring is associated with lower mortality in critically ill patients, however it is underutilized due to the difficulty of manually interpreting prolonged streams of cEEG data.

BIG-bench Machine Learning EEG +1

Modeling the Complex Dynamics and Changing Correlations of Epileptic Events

no code implementations • 27 Feb 2014 • Drausin F. Wulsin, Emily B. Fox, Brian Litt

A goal of our work is to parse these complex epileptic events into distinct dynamic regimes.

EEG