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David R Ledbetter

Showing results (1-10 of 11) with videos related to

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Critical Care Explorations|September 14, 2022
Predicting Time to Death After Withdrawal of Life-Sustaining Treatment in ChildrenMeredith C Winter, David R Ledbetter
Pediatric Critical Care Medicine : a Journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies|October 4, 2018
Artificial Intelligence: An Inkling of CautionRandall C Wetzel, Melissa Aczon, David R Ledbetter
Pediatric Critical Care Medicine : a Journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies|March 12, 2021
Continuous Prediction of Mortality in the PICU: A Recurrent Neural Network Model in a Single-Center DatasetMelissa D Aczon, David R Ledbetter, Eugene Laksana, et al.
Journal of the American Medical Informatics Association : JAMIA|June 13, 2023
Narrowing the gap: expected versus deployment performanceAlice X Zhou, Melissa D Aczon, Eugene Laksana, et al.
Journal of the American Medical Informatics Association : JAMIA|October 9, 2018
Predicting individual physiologically acceptable states at discharge from a pediatric intensive care unitCameron S Carlin, Long V Ho, David R Ledbetter, et al.
Scientific Reports|May 26, 2022
Development of a deep learning model that predicts Bi-level positive airway pressure failureDaniel D Im, Eugene Laksana, David R Ledbetter, et al.
Pediatric Critical Care Medicine : a Journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies|November 6, 2020
Machine Learning to Predict Cardiac Death Within 1 Hour After Terminal ExtubationMeredith C Winter, Travis E Day, David R Ledbetter, et al.
Journal of Intensive Care Medicine|December 18, 2023
Prehospitalization Trauma and Physiologic Factors Associated with the Presence of Post-traumatic Stress 3 Months After PICU DischargeAriya N Chau, Ryan A Eckberg, Eugene Laksana, et al.
Pediatric Critical Care Medicine : a Journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies|March 6, 2023
Analgesia and Sedation at Terminal Extubation: A Secondary Analysis From Death One Hour After Terminal Extubation Study DataSandeep Tripathi, Eugene Laksana, Michael C McCrory, et al.
Pediatric Critical Care Medicine : a Journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies|June 25, 2025
Death One Hour After Terminal Extubation in Children: Validation of a Machine Learning Model to Predict Cardiac Death After Withdrawal of Life-Sustaining Treatment in a Multicenter Cohort, 2009-2021Meredith C Winter, Alice X Zhou, Eugene Laksana, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
Critical Care Explorations|September 14, 2022
Predicting Time to Death After Withdrawal of Life-Sustaining Treatment in ChildrenMeredith C Winter, David R Ledbetter
Pediatric Critical Care Medicine : a Journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies|October 4, 2018
Artificial Intelligence: An Inkling of CautionRandall C Wetzel, Melissa Aczon, David R Ledbetter
Pediatric Critical Care Medicine : a Journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies|March 12, 2021
Continuous Prediction of Mortality in the PICU: A Recurrent Neural Network Model in a Single-Center DatasetMelissa D Aczon, David R Ledbetter, Eugene Laksana, et al.
Journal of the American Medical Informatics Association : JAMIA|June 13, 2023
Narrowing the gap: expected versus deployment performanceAlice X Zhou, Melissa D Aczon, Eugene Laksana, et al.
Journal of the American Medical Informatics Association : JAMIA|October 9, 2018
Predicting individual physiologically acceptable states at discharge from a pediatric intensive care unitCameron S Carlin, Long V Ho, David R Ledbetter, et al.
Scientific Reports|May 26, 2022
Development of a deep learning model that predicts Bi-level positive airway pressure failureDaniel D Im, Eugene Laksana, David R Ledbetter, et al.
Pediatric Critical Care Medicine : a Journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies|November 6, 2020
Machine Learning to Predict Cardiac Death Within 1 Hour After Terminal ExtubationMeredith C Winter, Travis E Day, David R Ledbetter, et al.
Journal of Intensive Care Medicine|December 18, 2023
Prehospitalization Trauma and Physiologic Factors Associated with the Presence of Post-traumatic Stress 3 Months After PICU DischargeAriya N Chau, Ryan A Eckberg, Eugene Laksana, et al.
Pediatric Critical Care Medicine : a Journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies|March 6, 2023
Analgesia and Sedation at Terminal Extubation: A Secondary Analysis From Death One Hour After Terminal Extubation Study DataSandeep Tripathi, Eugene Laksana, Michael C McCrory, et al.
Pediatric Critical Care Medicine : a Journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies|June 25, 2025
Death One Hour After Terminal Extubation in Children: Validation of a Machine Learning Model to Predict Cardiac Death After Withdrawal of Life-Sustaining Treatment in a Multicenter Cohort, 2009-2021Meredith C Winter, Alice X Zhou, Eugene Laksana, et al.
Pageof 2