David Shimabukuro

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Multicenter validation of a machine-learning algorithm for 48-h all-cause mortality prediction

Uli K. Chettipally, Grant S. Fletcher, P. Stark, 2019, Health Informatics J..

Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU

Uli K. Chettipally, Grant S. Fletcher, L. Shieh, 2018, BMJ Open.

Assessing Preventable Harms in the Intensive Care Unit: Data From a Tertiary Care Academic Medical Institution

David Shimabukuro, M. Matthay, N. Sung, 2018, American journal of medical quality : the official journal of the American College of Medical Quality.

Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach

Uli K. Chettipally, D. Wales, Thomas Desautels, 2016, JMIR medical informatics.

Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial

Ritankar Das, C. Barton, David Shimabukuro, 2017, BMJ Open Respiratory Research.

Fresh and Stored Red Blood Cell Transfusion Equivalently Induce Subclinical Pulmonary Gas Exchange Deficit in Normal Humans

R. Weiskopf, David Shimabukuro, M. Looney, 2012, Anesthesia and analgesia.

Rescue Therapies for Acute Hypoxemic Respiratory Failure

Linda L. Liu, David Shimabukuro, J. Aldrich, 2010, Anesthesia and analgesia.

Respiratory Complications and Management of Mechanical Ventilation in Cervical Spine Injury

David Shimabukuro, M. Kearns, 2012 .

Injury and repair in lung and airways.

David Shimabukuro, T. Sawa, M. Gropper, 2003, Critical care medicine.

O-Antigen Serotypes and Type III Secretory Toxins in Clinical Isolates of Pseudomonas aeruginosa

David Shimabukuro, K. Faure, J. Wiener-Kronish, 2003, Journal of Clinical Microbiology.

Chapter 3 – Cardiopulmonary Resuscitation

David Shimabukuro, 2013 .

Multicenter validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU

Uli K. Chettipally, Grant S. Fletcher, L. Shieh, 2018, bioRxiv.

Noisy mechanical ventilation: listen to the melody.

David Shimabukuro, M. Gropper, 2009, Anesthesiology.

Protocol-Based Management of Severe Sepsis and Septic Shock

David Shimabukuro, Anne L. Donovan, 2015, Current Anesthesiology Reports.

Effects of monoclonal anti-PcrV antibody on Pseudomonas aeruginosa-induced acute lung injury in a rat model

David Shimabukuro, N. Shime, K. Faure, 2003, Journal of immune based therapies and vaccines.

Relationship Between a Sepsis Intervention Bundle and In-Hospital Mortality Among Hospitalized Patients: A Retrospective Analysis of Real-World Data

David Shimabukuro, S. Shiboski, R. Gonzales, 2017, Anesthesia and analgesia.

Multicenter validation of a machine learning algorithm for 48 hour all-cause mortality prediction

Philip B. Stark, Christopher Barton, Hamid Mohamadlou, 2018, bioRxiv.

Cost and mortality impact of an algorithm-driven sepsis prediction system

Yaniv Kerem, Uli K. Chettipally, Ritankar Das, 2017, Journal of medical economics.

Acute Care Nurse Practitioners in an Academic Multidisciplinary ICU

David Shimabukuro, 2011 .

Chapter 32 – Sepsis, Severe Sepsis, and Septic Shock

David Shimabukuro, R. Savel, M. Gropper, 2013 .

Journal of Immune Based Therapies and Vaccines Effects of Monoclonal Anti-pcrv Antibody on Pseudomonas Aeruginosa-induced Acute Lung Injury in a Rat Model

David Shimabukuro, N. Shime, K. Faure, 2022 .