Artificial Intelligence in Emergency Medicine: A Literature Review
Introduction Artificial intelligence (AI) is rapidly transforming medical fields, particularly emergency medicine (EM), where timely decision-making is crucial. AI offers potential benefits in diagnostic accuracy, patient care optimization, and workflow efficiency within emergency departments (EDs)....
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| Language: | English |
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Nicolaus Copernicus University in Toruń
2024-11-01
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| Series: | Quality in Sport |
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| Online Access: | https://apcz.umk.pl/QS/article/view/55839 |
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| author | Gracjan Sitarek Marta Żerek |
| author_facet | Gracjan Sitarek Marta Żerek |
| author_sort | Gracjan Sitarek |
| collection | DOAJ |
| description | Introduction
Artificial intelligence (AI) is rapidly transforming medical fields, particularly emergency medicine (EM), where timely decision-making is crucial. AI offers potential benefits in diagnostic accuracy, patient care optimization, and workflow efficiency within emergency departments (EDs).
Purpose of Work
This review aims to synthesize recent advancements in AI applications within emergency medicine, focusing on diagnostic support, patient triage, clinical decision support systems (CDSS), and workflow optimization. Additionally, we highlight the potential benefits, challenges, and future directions for AI in EM.
Material and Methods
A comprehensive literature search was conducted using PubMed and Google Scholar databases. We reviewed peer-reviewed articles from 2008 to 2024, focusing on AI-driven solutions in EDs. Keywords included "artificial intelligence," "emergency medicine," "machine learning," and "clinical decision support." Studies were selected based on their relevance to AI applications in EM, diagnostic improvements, and operational efficiency.
The results highlight the promising role of AI in improving diagnostic accuracy, reducing overcrowding, optimizing triage processes, and addressing clinician workload. However, challenges like ethical concerns, data bias, and the need for clinical validation remain. Further research is necessary to integrate AI more effectively in clinical practice.
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| format | Article |
| id | doaj-art-3579078896ad48d28cfd643392d1c0b4 |
| institution | OA Journals |
| issn | 2450-3118 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nicolaus Copernicus University in Toruń |
| record_format | Article |
| series | Quality in Sport |
| spelling | doaj-art-3579078896ad48d28cfd643392d1c0b42025-08-20T02:23:05ZengNicolaus Copernicus University in ToruńQuality in Sport2450-31182024-11-013310.12775/QS.2024.33.55839Artificial Intelligence in Emergency Medicine: A Literature ReviewGracjan Sitarek0Marta Żerek1Uniwersytecki Szpital Kliniczny w Opolu, University of Opole, PolandUniwersytecki Szpital Kliniczny w Opolu, University of Opole, PolandIntroduction Artificial intelligence (AI) is rapidly transforming medical fields, particularly emergency medicine (EM), where timely decision-making is crucial. AI offers potential benefits in diagnostic accuracy, patient care optimization, and workflow efficiency within emergency departments (EDs). Purpose of Work This review aims to synthesize recent advancements in AI applications within emergency medicine, focusing on diagnostic support, patient triage, clinical decision support systems (CDSS), and workflow optimization. Additionally, we highlight the potential benefits, challenges, and future directions for AI in EM. Material and Methods A comprehensive literature search was conducted using PubMed and Google Scholar databases. We reviewed peer-reviewed articles from 2008 to 2024, focusing on AI-driven solutions in EDs. Keywords included "artificial intelligence," "emergency medicine," "machine learning," and "clinical decision support." Studies were selected based on their relevance to AI applications in EM, diagnostic improvements, and operational efficiency. The results highlight the promising role of AI in improving diagnostic accuracy, reducing overcrowding, optimizing triage processes, and addressing clinician workload. However, challenges like ethical concerns, data bias, and the need for clinical validation remain. Further research is necessary to integrate AI more effectively in clinical practice. https://apcz.umk.pl/QS/article/view/55839Artificial intelligenceemergency medicinehealthcare innovationAI ethics |
| spellingShingle | Gracjan Sitarek Marta Żerek Artificial Intelligence in Emergency Medicine: A Literature Review Quality in Sport Artificial intelligence emergency medicine healthcare innovation AI ethics |
| title | Artificial Intelligence in Emergency Medicine: A Literature Review |
| title_full | Artificial Intelligence in Emergency Medicine: A Literature Review |
| title_fullStr | Artificial Intelligence in Emergency Medicine: A Literature Review |
| title_full_unstemmed | Artificial Intelligence in Emergency Medicine: A Literature Review |
| title_short | Artificial Intelligence in Emergency Medicine: A Literature Review |
| title_sort | artificial intelligence in emergency medicine a literature review |
| topic | Artificial intelligence emergency medicine healthcare innovation AI ethics |
| url | https://apcz.umk.pl/QS/article/view/55839 |
| work_keys_str_mv | AT gracjansitarek artificialintelligenceinemergencymedicinealiteraturereview AT martazerek artificialintelligenceinemergencymedicinealiteraturereview |