Additional file 2 of Artificial intelligence-driven decision support for patients with acute respiratory failure: a scoping review

Supplementary material 2: Table 3. Data Extraction Sheet.

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Bibliographic Details
Main Author:	Preeti Gupta (22023547) (author)
Other Authors:	Alex K. Pearce (22023550) (author), Thaidan Pham (15465008) (author), Michael Miller (821) (author), Korey Brunetti (22023553) (author), Karen Heskett (12458338) (author), Atul Malhotra (328196) (author), Anoop Mayampurath (1345623) (author), Majid Afshar (4586263) (author)
Published:	2025
Subjects:	Artificial Intelligence and Image Processing Information Systems transform patient care systematic literature search acute respiratory failure performed quality assessment machine learning model clinically meaningful outcome 67 %) focused stage clinical evaluation none reported ai algorithmic fairness considerations 25 – 6 eligibility criteria studies compared models trained early clinical evaluation driven decision support decision support algorithmic fairness related outcome quality assessments model performance evaluated models ai criteria 50 %) driven intervention world implementation studies met studies meeting studies demonstrated statistically significant simulated settings related errors promising tool predicting weaning one study methodological rigor mechanical ventilation largely unaddressed january 2025 independently screened human factors health systems four studies critical aspects control group broader deployment artificial intelligence ai framework 987 citations
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