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Phenotyping COVID-19 respiratory failure in spontaneously breathing patients with AI on lung CT-scan.

Critical care (London, England) - 5 Aug 2024

Rezoagli Emanuele, Xin Yi, Signori Davide, Sun Wenli, Gerard Sarah, Delucchi Kevin L, Magliocca Aurora, Vitale Giovanni, Giacomini Matteo, Mussoni Linda, Montomoli Jonathan, Subert Matteo, Ponti Alessandra, Spadaro Savino, Poli Giancarla, Casola Francesco, Herrmann Jacob, Foti Giuseppe, Calfee Carolyn S, Laffey John, Bellani Giacomo, Cereda Maurizio

Abstract excerpt

BACKGROUND: Automated analysis of lung computed tomography (CT) scans may help characterize subphenotypes of acute respiratory illness. We integrated lung CT features measured via deep learning with clinical and laboratory data in spontaneously breathing subjects to enhance the identification of COVID-19 subphenotypes. METHODS: This is a multicenter observational cohort study in spontaneously breathing patients...

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Identifiers

PMID: 39103945
DOI: 10.1186/s13054-024-05046-3
PMCID: PMC11301830

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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