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Matthew M Ruppert

Showing results (1-10 of 36) with videos related to

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Current Opinion in Critical Care|November 10, 2021
Advances in artificial intelligence and deep learning systems in ICU-related acute kidney injuryTezcan Ozrazgat-Baslanti, Tyler J Loftus, Yuanfang Ren, et al.
Arxiv|March 22, 2023
Clinical Courses of Acute Kidney Injury in Hospitalized Patients: A Multistate AnalysisEsra Adiyeke, Yuanfang Ren, Ziyuan Guan, et al.
Scientific Reports|October 18, 2023
Clinical courses of acute kidney injury in hospitalized patients: a multistate analysisEsra Adiyeke, Yuanfang Ren, Ziyuan Guan, et al.
Critical Care Explorations|July 23, 2020
Improving the Intensive Care Patient Experience With Virtual Reality-A Feasibility StudyTriton L Ong, Matthew M Ruppert, Maisha Akbar, et al.
Surgery|January 13, 2021
Reinforcement learning in surgeryShounak Datta, Yanjun Li, Matthew M Ruppert, et al.
F1000Research|September 19, 2022
The effect of non-pharmacologic strategies on prevention or management of intensive care unit delirium: a systematic reviewJulie S Cupka, Haleh Hashemighouchani, Jessica Lipori, et al.
Journal of the American Medical Informatics Association : JAMIA|October 28, 2022
A framework for a consistent and reproducible evaluation of manual review for patient matching algorithmsAgrayan K Gupta, Suranga N Kasthurirathne, Huiping Xu, et al.
Critical Care Explorations|December 23, 2020
ICU Delirium-Prediction Models: A Systematic ReviewMatthew M Ruppert, Jessica Lipori, Sandip Patel, et al.
The Journal of Surgical Research|June 13, 2020
Added Value of Intraoperative Data for Predicting Postoperative Complications: The MySurgeryRisk PostOp ExtensionShounak Datta, Tyler J Loftus, Matthew M Ruppert, et al.
Annals of Surgery|July 15, 2021
Aligning Patient Acuity With Resource Intensity After Major Surgery: A Scoping ReviewTyler J Loftus, Jeremy A Balch, Matthew M Ruppert, et al.
Pageof 4

Showing results (1-10 of 36) with videos related to

Sort By:
Pageof 4
Current Opinion in Critical Care|November 10, 2021
Advances in artificial intelligence and deep learning systems in ICU-related acute kidney injuryTezcan Ozrazgat-Baslanti, Tyler J Loftus, Yuanfang Ren, et al.
Arxiv|March 22, 2023
Clinical Courses of Acute Kidney Injury in Hospitalized Patients: A Multistate AnalysisEsra Adiyeke, Yuanfang Ren, Ziyuan Guan, et al.
Scientific Reports|October 18, 2023
Clinical courses of acute kidney injury in hospitalized patients: a multistate analysisEsra Adiyeke, Yuanfang Ren, Ziyuan Guan, et al.
Critical Care Explorations|July 23, 2020
Improving the Intensive Care Patient Experience With Virtual Reality-A Feasibility StudyTriton L Ong, Matthew M Ruppert, Maisha Akbar, et al.
Surgery|January 13, 2021
Reinforcement learning in surgeryShounak Datta, Yanjun Li, Matthew M Ruppert, et al.
F1000Research|September 19, 2022
The effect of non-pharmacologic strategies on prevention or management of intensive care unit delirium: a systematic reviewJulie S Cupka, Haleh Hashemighouchani, Jessica Lipori, et al.
Journal of the American Medical Informatics Association : JAMIA|October 28, 2022
A framework for a consistent and reproducible evaluation of manual review for patient matching algorithmsAgrayan K Gupta, Suranga N Kasthurirathne, Huiping Xu, et al.
Critical Care Explorations|December 23, 2020
ICU Delirium-Prediction Models: A Systematic ReviewMatthew M Ruppert, Jessica Lipori, Sandip Patel, et al.
The Journal of Surgical Research|June 13, 2020
Added Value of Intraoperative Data for Predicting Postoperative Complications: The MySurgeryRisk PostOp ExtensionShounak Datta, Tyler J Loftus, Matthew M Ruppert, et al.
Annals of Surgery|July 15, 2021
Aligning Patient Acuity With Resource Intensity After Major Surgery: A Scoping ReviewTyler J Loftus, Jeremy A Balch, Matthew M Ruppert, et al.
Pageof 4