Exploring timely and safe discharge from ICU: a comparative study of machine learning predictions and clinical practices

Exploring timely and safe discharge from ICU: a comparative study of machine learning predictions and clinical practices

Abstract Background The discharge practices from the intensive care unit exhibit heterogeneity and the recognition of eligible patients for discharge is often delayed. Recognizing the importance of safe discharge, which aims to minimize readmission and mortality, we developed a dynamic machine-learn...

Full description

Saved in:
Bibliographic Details
Main Authors: Chao Ping Wu, Rachel Benish Shirley, Alex Milinovich, Kaiyin Liu, Eduardo Mireles-Cabodevila, Hassan Khouli, Abhijit Duggal, Anirban Bhattacharyya
Format: Article
Language:English
Published: SpringerOpen 2025-01-01
Series:Intensive Care Medicine Experimental
Subjects:
Machine learning
Critical care
ICU discharge practice
Decision support in ICU discharge
Online Access:https://doi.org/10.1186/s40635-025-00717-z
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s40635-025-00717-z

Similar Items