Journal article
Artificial intelligence and machine learning in emergency medicine: a narrative review
Acute medicine & surgery, Vol.9(1), pp.e740-e740
01/2022
DOI: 10.1002/ams2.740
PMCID: PMC8887797
PMID: 35251669
Abstract
The emergence and evolution of artificial intelligence (AI) has generated increasing interest in machine learning applications for health care. Specifically, researchers are grasping the potential of machine learning solutions to enhance the quality of care in emergency medicine.
We undertook a narrative review of published works on machine learning applications in emergency medicine and provide a synopsis of recent developments.
This review describes fundamental concepts of machine learning and presents clinical applications for triage, risk stratification specific to disease, medical imaging, and emergency department operations. Additionally, we consider how machine learning models could contribute to the improvement of causal inference in medicine, and to conclude, we discuss barriers to safe implementation of AI.
We intend that this review serves as an introduction to AI and machine learning in emergency medicine.
Details
- Title: Subtitle
- Artificial intelligence and machine learning in emergency medicine: a narrative review
- Creators
- Brianna Mueller - University of IowaTakahiro Kinoshita - Philips Research North America Cambridge Massachusetts USAAlexander Peebles - Roy J. and Lucille A. Carver College of MedicineMark A Graber - University of IowaSangil Lee - Roy J. and Lucille A. Carver College of Medicine
- Resource Type
- Journal article
- Publication Details
- Acute medicine & surgery, Vol.9(1), pp.e740-e740
- DOI
- 10.1002/ams2.740
- PMID
- 35251669
- PMCID
- PMC8887797
- NLM abbreviation
- Acute Med Surg
- ISSN
- 2052-8817
- eISSN
- 2052-8817
- Language
- English
- Date published
- 01/2022
- Academic Unit
- Emergency Medicine; Injury Prevention Research Center
- Record Identifier
- 9984297357602771
Metrics
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