Critical Care

Latest AI and machine learning research in critical care for healthcare professionals.

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Subcategories: Sepsis
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Improving robustness by action correction via multi-step maximum risk estimation.

Certifying robustness against external uncertainties throughout the control process to reduce the ri...

Prediction of Composite Clinical Outcomes for Childhood Neuroblastoma Using Multi-Omics Data and Machine Learning.

Neuroblastoma is a common malignant tumor in childhood that seriously endangers the health and lives...

Hope for the best prepare for the worst: acute kidney disease and catastrophic comorbidities (a case report).

It is evident that Acute Kidney Injury (AKI) is an independent risk factor for both the survival of ...

Noninvasive estimation of PaCO from volumetric capnography in animals with injured lungs: an Artificial Intelligence approach.

To investigate the feasibility of non-invasively estimating the arterial partial pressure of carbon ...

Impact of a trace mineral injection at weaning on growth, behavior, and inflammatory, antioxidant, and immune responses of beef calves.

Two experiments evaluated the effects of an injectable trace mineral (ITM) solution at weaning on tr...

The predictive value of heparin-binding protein for bacterial infections in patients with severe polytrauma.

INTRODUCTION: Heparin-binding protein is an inflammatory factor with predictive value for sepsis and...

Multi-modal cross-domain self-supervised pre-training for fMRI and EEG fusion.

Neuroimaging techniques including functional magnetic resonance imaging (fMRI) and electroencephalog...

Drug toxicity prediction model based on enhanced graph neural network.

Prediction of drug toxicity remains a significant challenge and an essential process in drug discove...

Machine learning for predicting acute myocardial infarction in patients with sepsis.

Acute myocardial infarction (AMI) and sepsis are the leading causes of high mortality rates in inten...

A 4D tensor-enhanced multi-dimensional convolutional neural network for accurate prediction of protein-ligand binding affinity.

Protein-ligand interactions are the molecular basis of many important cellular activities, such as g...

MCBERT: A multi-modal framework for the diagnosis of autism spectrum disorder.

Within the domain of neurodevelopmental disorders, autism spectrum disorder (ASD) emerges as a disti...

Artificial intelligence in respiratory care.

The evolution of artificial intelligence (AI) has revolutionised numerous aspects of our daily lives...

Machine learning analysis of CD4+ T cell gene expression in diverse diseases: insights from cancer, metabolic, respiratory, and digestive disorders.

CD4 T cells play a pivotal role in the immune system, particularly in adaptive immunity, by orchestr...

Machine learning for the prediction of mortality in patients with sepsis-associated acute kidney injury: a systematic review and meta-analysis.

BACKGROUND: Predicting mortality in sepsis-related acute kidney injury facilitates early data-driven...

MFC-ACL: Multi-view fusion clustering with attentive contrastive learning.

Multi-view clustering can better handle high-dimensional data by combining information from multiple...

Neural network-based dynamic target enclosing control for uncertain nonlinear multi-agent systems over signed networks.

Neural networks have significant advantages in the estimation of uncertainty dynamics, which can aff...

3D MFA: An automated 3D Multi-Feature Attention based approach for spine segmentation using a multi-stage network pruning.

Spine segmentation poses significant challenges due to the complex anatomical structure of the spine...

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