Article

Risk assessment of acute respiratory failure requiring advanced respiratory support using machine learning

2022-06-08

Abstract excerpt

<h4>Background: </h4> Acute respiratory failure (ARF) presents within a spectrum of clinical manifestations and illness severity, and mortality occurs in approximately 30% of patients who develop ARF. Early risk identification is imperative for implementation of prophylactic measures prior to ARF onset. In this study, we develop and validate a machine learning algorithm (MLA) to predict patients at risk of ARF req...

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Literature Corpus work: dbfb4cfb-a91f-5943-abc0-bd6435f9cefd
DOI: 10.21203/rs.3.rs-1668247/v1

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