ArticleJournal of Taibah University Medical Sciences2025
AI in critical care: A narrative review of prospective applications and future potential in KSA's health transformation 2030.
Article in Journal of Taibah University Medical Sciences, 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.
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Who cites it
2 citing papers in PubMed.
- Shifts in primary care utilization patterns following digital health implementation: an operational evaluation of the 2023-2024 Hajj mass gatherings.Frontiers in public health · 2026Observational
- Image recognition-based detection system for preventing accidental dislodgement of head-and-neck medical supplies in ICU patients: A feasibility randomized controlled trial.International journal of nursing sciences · 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
This narrative review explores the integration of artificial intelligence (AI) within critical care settings in KSA in alignment with the goals outlined in Saudi Vision 2030. As part of the Health Sector Transformation Program, the incorporation of AI technologies aims to enhance patient outcomes, optimize workflows, and improve the operational efficiency of intensive care units (ICUs). Key applications include automated clinical documentation, predictive analytics for early detection of clinical deterioration, and AI-assisted imaging techniques, such as chest X-ray and ultrasound interpretation. These innovations can support clinicians by reducing their administrative burden as well as enabling timely interventions, particularly in resource-constrained environments. In addition, AI-powered tele-ICU command centers are explored to extend critical care expertise to underserved regions and enhance equitable access to specialized care. This review was conducted using a structured narrative approach by synthesizing peer-reviewed literature, national policy documents, and expert perspectives from ICU physicians in KSA, Canada, and other international settings.
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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.