Early prediction of hemodynamic interventions in the intensive care unit using machine learning

Abstract Background Timely recognition of hemodynamic instability in critically ill patients enables increased vigilance and early treatment opportunities. We develop the Hemodynamic Stability Index (HSI), which highlights situational awareness of possible hemodynamic instability occurring at the be...

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Detalles Bibliográficos
Autores principales:	Asif Rahman, Yale Chang, Junzi Dong, Bryan Conroy, Annamalai Natarajan, Takahiro Kinoshita, Francesco Vicario, Joseph Frassica, Minnan Xu-Wilson
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Hemodynamics Vasoactive therapy Machine learning Clinical decision support Medical emergencies. Critical care. Intensive care. First aid RC86-88.9
Acceso en línea:	https://doaj.org/article/f6daea3bc6d949eda64325550cba9c99
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Early prediction of hemodynamic interventions in the intensive care unit using machine learning

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