ArticleCureus2025
Artificial Intelligence in Critical Care: Promise, Peril, and the Path Forward.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Ethical readiness and trust in artificial intelligence-assisted anaesthesia: A cross-sectional survey study among anaesthesia professionals in India.Indian journal of anaesthesia · 2026Article
- How do dialysis nurses and AI reason clinically? A scenario-based comparative study.BMC nursing · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is poised to transform critical care by enhancing clinical decision-making, predictive accuracy, and operational efficiency. This editorial explores the expanding role of AI in intensive care units (ICUs), highlighting emerging applications such as predictive analytics, diagnostic imaging, real-time monitoring, and clinical decision support systems. Alongside these advances, the integration of AI presents critical challenges related to ethical implementation, regulatory oversight, clinician trust, and data interoperability. Drawing from current case studies and healthcare trends, this perspective underscores AI's potential to improve patient outcomes and optimize resource utilization. However, without rigorous validation, transparent practices, and a firm commitment to patient-centered design, AI risks becoming a liability rather than an asset. Sustainable adoption will require interdisciplinary collaboration, continuous evaluation, and the preservation of human connection at the heart of technologically supported care.
Indexed as
Identifiers
What OpenQuestion holds
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.