Predicting patient decompensation from continuous physiologic monitoring in the emergency department
Abstract Anticipation of clinical decompensation is essential for effective emergency and critical care. In this study, we develop a multimodal machine learning approach to predict the onset of new vital sign abnormalities (tachycardia, hypotension, hypoxia) in ED patients with normal initial vital...
Main Authors: | Sameer Sundrani, Julie Chen, Boyang Tom Jin, Zahra Shakeri Hossein Abad, Pranav Rajpurkar, David Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-04-01
|
Series: | npj Digital Medicine |
Online Access: | https://doi.org/10.1038/s41746-023-00803-0 |
Similar Items
-
Impact of emergency department‐based intensive care unit on outcomes of decompensating boarding emergency department patients
by: Jessica Doan, et al.
Published: (2023-10-01) -
Prognostic value of the NEWS + Lactate score in patients with decompensated heart failure in the emergency department
by: Mustafa Can Guzelce, et al.
Published: (2023-12-01) -
Challenges in the Management of Acutely Decompensated Congestive Heat Failure: Disposition Decisions in the Emergency Department
by: Kirk, J. Douglas, et al.
Published: (2003-04-01) -
Predictors of acute kidney injury in patients with acute decompensated heart failure in emergency departments in China
by: Hongxia Ge, et al.
Published: (2021-09-01) -
Development and validation of an early warning tool for sepsis and decompensation in children during emergency department triage
by: Louis Ehwerhemuepha, et al.
Published: (2021-04-01)