AIMC Journal:
Intensive care medicine experimental

Showing 1 to 10 of 18 articles

Development and evaluation of machine learning-based prediction-modelling for initial vancomycin serum concentrations in septic ICU patients using clinical health record data.

Intensive care medicine experimental Sep 23, 2026
BACKGROUND: Sepsis remains a life-threatening condition with highly heterogeneous and dynamic pathophysiology, limiting the effectiveness of uniform therapeutic strategies. Beyond timely source control, antimicrobial therapy represents the only causa...
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Automated hemodynamic resuscitation system for computer-controlled norepinephrine, vasopressin, and fluid therapy in endotoxin-induced shock: a feasibility and physiological proof-of-concept study.

Intensive care medicine experimental Sep 20, 2026
BACKGROUND: To support hemodynamic management in vasoplegic shock, we previously developed a closed-loop automated infusion system of norepinephrine (NE) and fluid to automatically restore arterial pressure (AP) and cardiac output (CO). To enhance th...
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Leveraging ECG foundation models in critical care for sinus rhythm and atrial fibrillation classification.

Intensive care medicine experimental Aug 26, 2026
BACKGROUND: Recent advances in deep learning have led to the development of ECG foundation models (ECG-FMs) trained with self-supervised learning, which can extract generalizable representations from large-scale data. In this study, we evaluated the ...
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Leashing heterogeneous sepsis with phenotype-informed decision support modeling.

Intensive care medicine experimental Jul 15, 2026
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Machine learning models predicting extubation success in mechanically ventilated patients: a systematic review and meta-analysis.

Intensive care medicine experimental Jul 9, 2026
BACKGROUND: Optimal timing of extubation in mechanically ventilated patients remains a major challenge in intensive care. Machine learning (ML) models have been increasingly proposed to support clinical decision-making, yet their predictive performan...
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Improving mortality prediction in critically ill cancer patients with a multidimensional machine learning model.

Intensive care medicine experimental Jul 1, 2026
BACKGROUND: Prognostic assessment in critically ill cancer patients is challenging due to the suboptimal performance of traditional severity scores. We developed and validated machine learning models to provide an objective triage and risk-stratifica...
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Behaviour artificial intelligence technology to support the decision-making process of continuation or withdrawal of life-sustaining therapy.

Intensive care medicine experimental Jul 1, 2026
BACKGROUND: Withholding and withdrawing life-sustaining therapy (LST) is common in European ICUs but significant variations exist. Behaviour artificial intelligence technology (BAIT) may help standardize the ethical dilemma to continue or withdraw LS...
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Mass cytometry reveals complex neutrophil heterogeneity in patients with severe sepsis.

Intensive care medicine experimental Jun 11, 2026
RATIONALE: Sepsis is a state of life-threatening organ dysfunction in the setting of infection. It is biologically heterogeneous, as evidenced by whole blood transcriptomic analyses that reveal distinct molecular subtypes based on gene expression. At...
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Prospective and external evaluation of an AI model for continuous and early prediction of moderate and severe AKI in critically ill patients.

Intensive care medicine experimental Jun 10, 2026
BACKGROUND: Acute kidney injury (AKI) is a major complication in critically ill patients, burdening both patients and healthcare systems. We previously introduced an AI-based model for early and continuous prediction of ICU-acquired AKI (ICU-A-AKI-2/...
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Acute brain dysfunction clusters in COVID-19: a pilot machine learning-based analysis of the COVID-D cohort.

Intensive care medicine experimental Jun 8, 2026
PURPOSE: While acute brain dysfunction (ABD, i.e., delirium and coma) is associated with significantly increased morbidity in critically ill patients, it presents with great heterogeneity that poses a challenge for management and prognostication. Whi...
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