ArticleiScience2023
Artificial intelligence and machine learning in prehospital emergency care: A scoping review.
Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- Machine learning assisted differentiation of low acuity patients at dispatch: The MADLAD randomized controlled trial.PLoS medicine · 2026Trial
- Real-time prediction of trauma-induced coagulopathy using an inverted transformer (trauma-former): a methodological feasibility and simulation study based on the ADEMP framework.BMC medical research methodology · 2026Article
- Artificial intelligence in prehospital assessment of acute coronary syndrome: a scoping review.BMC emergency medicine · 2026Article
- The Future of Artificial Intelligence in Emergency Medical Services by 2030: An International Consensus Report.Journal of the American College of Emergency Physicians open · 2026Article
- Digital emergency routing: analysis of feasibility, utilization, and equity implications.Israel journal of health policy research · 2026Article
- Evaluating the real-world utility of four physiological scores for prehospital interventions in resource-limited EMS systems: a population-based study of 15,720 cases.BMC health services research · 2026Article
- Communication Surrounding Treatment Preferences for Older Adults With Dementia During Emergency Medical Services Response.Journal of the American Geriatrics Society · 2026Article
- Rapid trauma classification under data scarcity: an emergency on-scene decision model combining natural language processing and machine learning.Medical & biological engineering & computing · 2025Article
- Review
- Emergency medical services providers' perspectives on the use of artificial intelligence in prehospital identification of stroke- a qualitative study in Norway and Sweden.BMC emergency medicine · 2025Article
- Bridging Data Gaps in Emergency Care: The NIGHTINGALE Project and the Future of AI in Mass Casualty Management.Journal of medical Internet research · 2025Article
- Advancing a machine learning-based decision support tool for pre-hospital assessment of dyspnoea by emergency medical service clinicians: a retrospective observational study.BMC emergency medicine · 2025Observational
- Artificial Intelligence in Cardiopulmonary Resuscitation: Revolutionizing Resuscitation Through Precision and Prediction - A Narrative Review.Vascular health and risk management · 2025Review
- Current Applications, Challenges, and Future Directions of Artificial Intelligence in Emergency Medicine: A Narrative Review.Archives of academic emergency medicine · 2025Article
- Utilising artificial intelligence in prehospital emergency care systems in low- and middle-income countries: a scoping review.Frontiers in public health · 2025Article
- Use of artificial intelligence to support prehospital traumatic injury care: A scoping review.Journal of the American College of Emergency Physicians open · 2024Article
- Pre-Hospital Stroke Care beyond the MSU.Current neurology and neuroscience reports · 2024Review
- Enhancing Trauma Care: A Machine Learning Approach with XGBoost for Predicting Urgent Hemorrhage Interventions Using NTDB Data.Bioengineering (Basel, Switzerland) · 2024Article
- The Future of CPR: Leveraging Artificial Intelligence for Enhanced Cardiopulmonary Resuscitation Outcomes.The journal of Tehran Heart Center · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Our scoping review provides a comprehensive analysis of the landscape of artificial intelligence (AI) applications in prehospital emergency care (PEC). It contributes to the field by highlighting the most studied AI applications and identifying the most common methodological approaches across 106 included studies. The findings indicate a promising future for AI in PEC, with many unique use cases, such as prognostication, demand prediction, resource optimization, and the Internet of Things continuous monitoring systems. Comparisons with other approaches showed AI outperforming clinicians and non-AI algorithms in most cases. However, most studies were internally validated and retrospective, highlighting the need for rigorous prospective validation of AI applications before implementation in clinical settings. We identified knowledge and methodological gaps using an evidence map, offering a roadmap for future investigators. We also discussed the significance of explainable AI for establishing trust in AI systems among clinicians and facilitating real-world validation of AI models.
Indexed as
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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.