Novel Machine Learning Approach to Predict and Personalize Length of Stay for Patients Admitted with Syncope from the Emergency Department

Novel Machine Learning Approach to Predict and Personalize Length of Stay for Patients Admitted with Syncope from the Emergency Department

<b>Background</b>: Syncope, a common problem encountered in the emergency department (ED), has a multitude of causes ranging from benign to life-threatening. Hospitalization may be required, but the management can vary substantially depending on specific clinical characteristics. Models...

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Bibliographic Details
Main Authors: Sangil Lee, Avinash Reddy Mudireddy, Deepak Kumar Pasupula, Mehul Adhaduk, E. John Barsotti, Milan Sonka, Giselle M. Statz, Tyler Bullis, Samuel L. Johnston, Aron Z. Evans, Brian Olshansky, Milena A. Gebska
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Journal of Personalized Medicine
Subjects:
syncope
length of stay
artificial intelligence
machine learning
prediction
Online Access:https://www.mdpi.com/2075-4426/13/1/7

Internet

https://www.mdpi.com/2075-4426/13/1/7

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