Machine Learning Classifier Models: The Future for Acute Respiratory Distress Syndrome Phenotyping?-Reference-Cited by-同舟云学术

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Machine Learning Classifier Models: The Future for Acute Respiratory Distress Syndrome Phenotyping?

Published:2020-10-01 Issue:7 Volume:202 Page:919-920
ISSN:1073-449X
Container-title:American Journal of Respiratory and Critical Care Medicine
language:en
Short-container-title:Am J Respir Crit Care Med

Author:

McNicholas Bairbre¹^ORCID,Madden Michael G.²,Laffey John G.¹³⁴^ORCID

Affiliation:

1. Department of Anaesthesia and Intensive Care Medicine, Galway University Hospitals, Galway, Ireland

2. College of Science and Engineering, National University of Ireland, Galway, Ireland

3. School of Medicineand

4. Regenerative Medicine Institute at the CURAM Centre for Medical Devices, National University of Ireland, Galway, Ireland

Publisher

American Thoracic Society

Subject

Critical Care and Intensive Care Medicine,Pulmonary and Respiratory Medicine

Reference13 articles.

1. Lessons to learn from epidemiologic studies in ARDS

2. Epidemiology, Patterns of Care, and Mortality for Patients With Acute Respiratory Distress Syndrome in Intensive Care Units in 50 Countries

3. Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials

4. Acute Respiratory Distress Syndrome Subphenotypes Respond Differently to Randomized Fluid Management Strategy

5. Acute respiratory distress syndrome subphenotypes and differential response to simvastatin: secondary analysis of a randomised controlled trial

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1. Identifying novel clinical phenotypes of acute respiratory distress syndrome using trajectories of daily fluid balance: a secondary analysis of randomized controlled trials;European Journal of Medical Research;2024-05-28

2. Advances in Biomarkers for Diagnosis and Treatment of ARDS;Diagnostics;2023-10-24

3. Clinical Sepsis Phenotypes in Critically Ill Patients;Microorganisms;2023-08-27

4. Longitudinal phenotypes in patients with acute respiratory distress syndrome: a multi-database study;Critical Care;2022-11-04

5. Artificial intelligence in identifying COVID-19 patients based on inflammatory parameters;2022 11th Mediterranean Conference on Embedded Computing (MECO);2022-06-07

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