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

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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Bibliographic Details
Main Authors: Asif Rahman, Yale Chang, Junzi Dong, Bryan Conroy, Annamalai Natarajan, Takahiro Kinoshita, Francesco Vicario, Joseph Frassica, Minnan Xu-Wilson
Format: article
Language:EN
Published: BMC 2021
Subjects:
Hemodynamics
Vasoactive therapy
Machine learning
Clinical decision support
Medical emergencies. Critical care. Intensive care. First aid
RC86-88.9
Online Access:https://doaj.org/article/f6daea3bc6d949eda64325550cba9c99
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https://doaj.org/article/f6daea3bc6d949eda64325550cba9c99

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