Innovative Methods for Real-time Risk Modeling of Postoperative Complications
This research will address the current critical challenge of post-operative complication prediction using real time intraoperative data and novel modeling methods. At a broader level, this work will improve the greater clinical research infrastructure at University of Minnesota for other use cases of real time clinical data, as well as provide infrastructure for contemporaneous feedback needed to realize a learning healthcare system and real time patient care improvement.
Goals & Aims
This work is funded by NIH National Institute of General Medical Sciences grant R01GM120079.
The BioMedical Information Collection and Understanding System (BioMedICUS) leverages open source solutions for text analysis and provides new analytic tools for processing and analyzing text of biomedical and clinical reports.