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Brian Murray

Verified
Los Angeles
As seen in: Hearst, MSN, MSN Canada, MSN India, MSN UK, Yahoo Entertainment, Yahoo Life, Color Research & Application, Forbes, MSN South Africa, Wiley and
Instagram: brianmurray7
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Articles

Machine Learning‐Based Prediction of Prolonged Duration of Mechanical Ventilation Using Medication Data

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By Brian Murray Verified, Bokai Zhao, Zhetao Chen, Susan Smith
| ACCP JOURNALS
Conflicts of Interest The authors declare no conflicts of interest. Data Availability Statement The data underlying the findings of this study are not publicly archived but are available from the corresponding author upon reasonable request. All data supporting the results are included within the article and its . Supporting Information Filename Description phar70090-sup-0001-Supinfo1.docxWord 2007 document , 958.8 KB Data S1: phar70090-sup-0001-Supinfo1.docx.
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Substance Withdrawal

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By Brian Murray Verified, Joshua L. Bacon
| Clinician.com Verified
By Joshua L. Bacon, DO, and Brian Patrick Murray, DO Withdrawal syndromes are common, high-acuity presentations in the emergency department (ED), arising after abrupt cessation or reduction of chronically used substances. They range from mild discomfort to life-threatening complications, such as seizures, delirium tremens, or severe autonomic instability. Alcohol, opioids, benzodiazepines/barbiturates, and antidepressants constitute the majority of withdrawal-related ED visits.
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The Measure of AI: An ABCDEF Framework for Critical Care Clinicians

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By Brian Murray Verified, Erin F. Barreto, Seth Bauer, Susan Smith
| Health Management Verified
Artificial intelligence holds unprecedented potential to transform healthcare, yet the current evidence base for AI applications in critical care remains limited. This article presents the ABCDEF framework to guide critical care clinicians in evaluating AI-based tools and demonstrate safety and effectiveness in real-world clinical environments.
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