Predicting Do-Not-Resuscitate Decisions in Critically Ill Patients Through Using Multitask Learning: A Retrospective Study of the MIMIC-IV Database.

Timely identification of critically ill patients for do-not-resuscitate (DNR) decisions is crucial to support shared decision-making and ethical end-of-life care. This study developed an explainable multitask learning (MTL) model using the MIMIC-IV database to predict the DNR decision within 24 h. T...

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Bibliographic Details
Published in:	Inquiry (00469580) Vol. 63; pp. 1 - 11
Main Authors:	Lin, Ming-Yen, Yeh, Chuan-Feng, Chao, Wen-Cheng
Format:	Article
Published:	Sage Publications Inc. 2/21/2026
Subjects:	Databases Do-not-resuscitate orders Prediction models Receiver operating characteristic curves Research funding Nursing assessment Decision making Catastrophic illness Retrospective studies Mann Whitney U Test Descriptive statistics Chi-squared test Longitudinal method Medical records Acquisition of data Intensive care units Length of stay in hospitals Data analysis software Critically ill patient psychology
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