Article

Generalizing intensive care AI across time scales in resource-limited settings

2026-04-24

Abstract excerpt

Generalization remains a major barrier to the clinical deployment of artificial intelligence in critical care. Models developed using high-frequency physiological monitoring often experience performance degradation when applied across hospitals, patient populations, and monitoring environments that differ from those used during training. Although variability in temporal resolution is widespread in critical care, i...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 57806e0d-4318-53da-909b-9b639d6db780
DOI: 10.64898/2026.04.23.26351588

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Generalizing intensive care AI across time scales in resource-limited settingsDOI 10.64898/2026.04.23.26351588Read

A Foundation Model for Intensive Care: Unlocking Generalization across Tasks and Domains at ScaleSemantic proximity Read

Development and Prospective Validation of Predictive Model for Early Hemodynamic Deterioration in Critical Care: A Multicenter StudySemantic proximity Read

Deep Temporal-Sepsis: A Calibrated Transformer Framework for Early ICU Sepsis Prediction with Grad-CAM Temporal PhenotypingSemantic proximity Read

Contrastive Transformer-Driven Discovery of Temporal Hemodynamic Subphenotypes in Cardiac Surgery PatientsSemantic proximity Read

Can machine learning or deep learning discover novel signatures of illness in continuous cardiorespiratory monitoring data?Semantic proximity Read

Non-invasive intracranial pressure waveform reconstruction with deep learningSemantic proximity Read

Continuous Patient State Attention ModelsSemantic proximity Read

Vitabel: Bridging Clinical Expertise and the Machine Learning Pipeline in Critical CareSemantic proximity Read

Cardiovascular and Autonomic Phenotypes Reveal Distinct Mechanisms of Sepsis Decompensation via Deep LearningSemantic proximity Read

Generalized Prediction of Hemodynamic Shock in Intensive Care UnitsSemantic proximity Read

Monitoring Fetal Heart Rate based on Fine-tuned Transfer Learning and Hybrid ModelsSemantic proximity Read

Non-Invasive Arterial Blood Pressure Waveform Generation in Critically Ill Patients: A Sensor-Based Deep Learning ApproachSemantic proximity Read