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Science fiction or clinical reality: a review of the applications of artificial intelligence along the continuum of trauma care.
- Source :
- World Journal of Emergency Surgery; 3/6/2023, Vol. 18 Issue 1, p1-23, 23p
- Publication Year :
- 2023
-
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. [ABSTRACT FROM AUTHOR]
- Subjects :
- INJURY risk factors
TRAUMATOLOGY diagnosis
TRAUMA surgery
INJURY complications
DECISION trees
MEDICAL triage
NATURAL language processing
ARTIFICIAL intelligence
MACHINE learning
RANDOM forest algorithms
AUTOMATIC speech recognition
CONTINUUM of care
RISK assessment
EMERGENCY medical services
DECISION making
LOGISTIC regression analysis
ARTIFICIAL neural networks
COMPUTER-aided diagnosis
WOUNDS & injuries
EMERGENCY medicine
DISCHARGE planning
Subjects
Details
- Language :
- English
- ISSN :
- 17497922
- Volume :
- 18
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- World Journal of Emergency Surgery
- Publication Type :
- Academic Journal
- Accession number :
- 162258394
- Full Text :
- https://doi.org/10.1186/s13017-022-00469-1