Artificial intelligence algorithm to predict the need for critical care in prehospital emergency medical services

Background In emergency medical services (EMSs), accurately predicting the severity of a patient’s medical condition is important for the early identification of those who are vulnerable and at high-risk. In this study, we developed and validated an artificial intelligence (AI) algorithm based on de...

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Veröffentlicht in:	Scandinavian journal of trauma, resuscitation and emergency medicine Jg. 28; H. 1; S. 17 - 8
Hauptverfasser:	Kang, Da-Young, Cho, Kyung-Jae, Kwon, Oyeon, Kwon, Joon-myoung, Jeon, Ki-Hyun, Park, Hyunho, Lee, Yeha, Park, Jinsik, Oh, Byung-Hee
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 04.03.2020 BioMed Central Ltd Springer Nature B.V BMC
Schlagworte:	Algorithms Artificial intelligence Blood pressure Body temperature Critical care Critical care medicine Deep learning Emergency medical care Emergency medical service Emergency medical services Emergency Medicine Emergency services Heart rate Hospital emergency services Hospitals Medical care needs assessment Medical research Medicine Medicine & Public Health Methods Original Research Patients Technology application Time Traumatic Surgery Triage Vital signs South Korea Deep learning Triage Emergency medical service Artificial intelligence
ISSN:	1757-7241, 1757-7241
Online-Zugang:	Volltext
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