ReviewWorld journal of critical care medicine2025
Utilizing artificial intelligence as an arbitrary tool in managing difficult COVID-19 cases in critical care medicine.
Review in World journal of critical care medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This opinion review paper explores the application of artificial intelligence (AI) as a decisive tool in managing complex coronavirus disease 2019 (COVID-19) cases within critical care medicine. Available data have shown that very severe cases required intensive care, most of which required endotracheal intubation and mechanical ventilation to avoid a lethal outcome if possible. The unprecedented challenges posed by the COVID-19 pandemic necessitate innovative approaches to patient care. AI offers significant potential in enhancing diagnostic accuracy, predicting patient outcomes, and optimizing treatment strategies. By analyzing vast amounts of clinical data, AI can support healthcare professionals in making informed decisions, thus improving patient outcomes. We also focus on current technologies, their implementation in critical care settings, and their impact on patient management during the COVID-19 crisis. Future directions for AI integration in critical care are also discussed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.