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This paper is in the following e-collection/theme issue:

Machine Learning (2987) Clinical Information and Decision Making (3450) Decision Support for Health Professionals (2072) Safety and Error Prevention in Health (302) Artificial Intelligence (4442) Intensive Care Unit (ICU) (182) Clinical Decision Support for Anesthesiology (23)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63601, first published .
Elderly man in hospital bed with oxygen mask, medical equipment visible

Predicting Agitation-Sedation Levels in Intensive Care Unit Patients: Development of an Ensemble Model

Predicting Agitation-Sedation Levels in Intensive Care Unit Patients: Development of an Ensemble Model

Authors of this article:

Pei-Yu Dai1 Author Orcid Image ;   Pei-Yi Lin2 Author Orcid Image ;   Ruey-Kai Sheu3 Author Orcid Image ;   Shu-Fang Liu2 Author Orcid Image ;   Yu-Cheng Wu4 Author Orcid Image ;   Chieh-Liang Wu4, 5 Author Orcid Image ;   Wei-Lin Chen2, 3 Author Orcid Image ;   Chien-Chung Huang6 Author Orcid Image ;   Guan-Yin Lin2 Author Orcid Image ;   Lun-Chi Chen7 Author Orcid Image
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Journals

  1. Zhang K, Wang Z, Zang S, Li Z, Zhao H, Li J, Lin F, Zhao H. A Hierarchical Multimodal Framework for Sedation Monitoring in ICU Patients. IEEE Transactions on Biomedical Engineering 2026;73(6):2227 View