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Frontiers in Physiology|May 1, 2023
Predicting respiratory decompensation in mechanically ventilated adult ICU patientsYvette Tan, Michael Young, Akanksha Girish, et al.
Paediatric Anaesthesia|May 22, 2023
A machine-learning approach for decision support and risk stratification of pediatric perioperative patients based on the APRICOT datasetGeoffrey M Gray, Luis M Ahumada, Mohamed A Rehman, et al.
American Journal of Infection Control|November 6, 2024
Identifying high-risk central lines in critically ill children: A novel nurse-driven screening and mitigation intervention to reduce CLABSIStephanie Morgenstern, Katie Thompson, Stephanie Panton, et al.
JAMA Pediatrics|December 13, 2016
Association of a Clinical Practice Guideline With Blood Culture Use in Critically Ill ChildrenCharlotte Z Woods-Hill, James Fackler, Kristen Nelson McMillan, et al.
Critical Care Research and Practice|June 2, 2018
Design and Deployment of a Pediatric Cardiac Arrest Surveillance SystemJordan Michel Duval-Arnould, Heather Marie Newton, Leann McNamara, et al.
Journal of Patient Safety|March 2, 2026
An Observational Study of Disparities in Voluntary Event Reporting in a Large Academic Health SystemEllen Pittman, Miranda R Jones, Katherine Hoops, et al.
Resuscitation|February 22, 2023
A pilot study to predict cardiac arrest in the pediatric intensive care unitAdam L Kenet, Rahul Pemmaraju, Sejal Ghate, et al.
Frontiers in Pediatrics|November 25, 2021
Predicting Flow Rate Escalation for Pediatric Patients on High Flow Nasal Cannula Using Machine LearningJoshua A Krachman, Jessica A Patricoski, Christopher T Le, et al.
Journal of the American Heart Association|December 19, 2018
Improved Cardiopulmonary Resuscitation Performance With CODE ACES2: A Resuscitation Quality BundleElizabeth A Hunt, Justin Jeffers, LeAnn McNamara, et al.
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