Artificial intelligence assists junior clinicians in assessing risk of severe cardio-respiratory instability in monitored patients - Robotics Institute Carnegie Mellon University

Artificial intelligence assists junior clinicians in assessing risk of severe cardio-respiratory instability in monitored patients

L. Chen, T. Pellathy, J. Yoon, G. Clermont, M. R. Pinsky, M. Hravnak, and A. Dubrawski
Journal Article, Intensive Care Medicine Experimental, Vol. 7, pp. 416, September, 2019

BibTeX

@article{Chen-2019-121675,
author = {L. Chen and T. Pellathy and J. Yoon and G. Clermont and M. R. Pinsky and M. Hravnak and A. Dubrawski},
title = {Artificial intelligence assists junior clinicians in assessing risk of severe cardio-respiratory instability in monitored patients},
journal = {Intensive Care Medicine Experimental},
year = {2019},
month = {September},
volume = {7},
pages = {416},
}
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.