Predicting 30-day survival after in-hospital cardiac arrest: a nationwide cohort study using machine learning and SHAP analysis

Predicting 30-day survival after in-hospital cardiac arrest: a nationwide cohort study using machine learning and SHAP analysis

Objective In-hospital cardiac arrest (IHCA) presents a critical challenge with low survival rates and limited prediction tools. Despite advances in resuscitation, predicting 30-day survival remains difficult, and current methods lack interpretability for timely decision-making. This study developed...

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Main Authors: Truls Råmunddal, Mats Borjesson, Erik Andersson, Per Nordberg, Kristofer Skoglund, Johan Herlitz, Araz Rawshani, Therese Djärv, Aidin Rawshani, Peter Lundgren, Antros Louca, Vibha Gupta, Joakim Sundström, Carl Magnusson
Format: Article
Language:English
Published: BMJ Publishing Group 2025-04-01
Series:BMJ Open
Online Access:https://bmjopen.bmj.com/content/15/4/e090493.full
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https://bmjopen.bmj.com/content/15/4/e090493.full

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