ReviewWorld journal of emergency surgery : WJES2023
Science fiction or clinical reality: a review of the applications of artificial intelligence along the continuum of trauma care.
Review in World journal of emergency surgery : WJES, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- Artificial intelligence in orthopedic trauma surgery: a scoping review of current applications and research gaps.Archives of orthopaedic and trauma surgery · 2026Article
- Artificial intelligence for early diagnosis in emergency department.Journal of anesthesia, analgesia and critical care · 2026Review
- Advancements in smart healthcare in emergency trauma care: from intelligent triage to prognostic prediction.Frontiers in public health · 2026Review
- The Clinical Significance of the Manchester Colour Wheel in a Sample of People Treated for Insured Injuries.Journal of clinical medicine · 2025Article
- Revolutionizing emergency care: an overview of the transformative role of artificial intelligence in diagnosis, triage, and patient management.International journal of emergency medicine · 2025Review
- Domain validation of the CRASH prognostic model for predicting 14-day mortality among patients and traumatic brain injury and intracranial hemorrhage in a Thai emergency department.International journal of emergency medicine · 2025Article
- Comparison of machine learning and human prediction to identify trauma patients in need of hemorrhage control resuscitation (ShockMatrix study): a prospective observational study.The Lancet regional health. Europe · 2025Article
- Ethical considerations on the role of artificial intelligence in defining the futility in emergency surgery.International journal of surgery (London, England) · 2025Article
- Review
- Are crystalloid-based fluid expansion strategies still relevant in the first hours of trauma induced hemorrhagic shock?Critical care (London, England) · 2024Review
- Pilot deployment of a machine-learning enhanced prediction of need for hemorrhage resuscitation after trauma - the ShockMatrix pilot study.BMC medical informatics and decision making · 2024Article
- Use of artificial intelligence to support prehospital traumatic injury care: A scoping review.Journal of the American College of Emergency Physicians open · 2024Article
- Artificial Intelligence-Enhanced Neurocritical Care for Traumatic Brain Injury : Past, Present and Future.Journal of Korean Neurosurgical Society · 2024Article
- Drinking from the Holy Grail-Does a Perfect Triage System Exist? And Where to Look for It?Journal of personalized medicine · 2024Review
- Artificial Intelligence in Optimizing the Functioning of Emergency Departments; a Systematic Review of Current Solutions.Archives of academic emergency medicine · 2024Review
- Automated volumetric evaluation of intracranial compartments and cerebrospinal fluid distribution on emergency trauma head CT scans to quantify mass effect.Frontiers in neuroscience · 2024Article
- Role of Artificial Intelligence in Global Surgery: A Review of Opportunities and Challenges.Cureus · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) and machine learning describe a broad range of algorithm types that can be trained based on datasets to make predictions. The increasing sophistication of AI has created new opportunities to apply these algorithms within within trauma care. Our paper overviews the current uses of AI along the continuum of trauma care, including injury prediction, triage, emergency department volume, assessment, and outcomes. Starting at the point of injury, algorithms are being used to predict severity of motor vehicle crashes, which can help inform emergency responses. Once on the scene, AI can be used to help emergency services triage patients remotely in order to inform transfer location and urgency. For the receiving hospital, these tools can be used to predict trauma volumes in the emergency department to help allocate appropriate staffing. After patient arrival to hospital, these algorithms not only can help to predict injury severity, which can inform decision-making, but also predict patient outcomes to help trauma teams anticipate patient trajectory. Overall, these tools have the capability to transform trauma care. AI is still nascent within the trauma surgery sphere, but this body of the literature shows that this technology has vast potential. AI-based predictive tools in trauma need to be explored further through prospective trials and clinical validation of algorithms.
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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.