Critical Care

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

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Subcategories: Sepsis
Showing 463-483 of 7,420 articles
CRISP: A causal relationships-guided deep learning framework for advanced ICU mortality prediction.

BACKGROUND: Mortality prediction is critical in clinical care, particularly in intensive care units ...

Multi-scale convolutional transformer network for motor imagery brain-computer interface.

Brain-computer interface (BCI) systems allow users to communicate with external devices by translati...

A comprehensive framework for multi-modal hate speech detection in social media using deep learning.

As social media platforms evolve, hate speech increasingly manifests across multiple modalities, inc...

Multi-scale prototype convolutional network for few-shot semantic segmentation.

Few-shot semantic segmentation aims to accurately segment objects from a limited amount of annotated...

Synthesis and Machine Learning Prediction of High Entropy Multi-Principal Element Nanoparticles.

The vast compositional space of multi-principal element nanoparticles (MPENs), along with their uniq...

Driving scene image Dehazing model based on multi-branch and multi-scale feature fusion.

Image dehazing is critical for enhancing image quality in applications such as autonomous driving, s...

HALSR-Net: Improving CNN Segmentation of Cardiac Left Ventricle MRI with Hybrid Attention and Latent Space Reconstruction.

Accurate cardiac MRI segmentation is vital for detailed cardiac analysis, yet the manual process is ...

Video-based multi-target multi-camera tracking for postoperative phase recognition.

PURPOSE: Deep learning methods are commonly used to generate context understanding to support surgeo...

Integrated multi-omics analysis and machine learning refine molecular subtypes and clinical outcome for hepatocellular carcinoma.

The high morbidity and mortality of hepatocellular carcinoma (HCC) impose a substantial economic bur...

Exploring unified cross-view hypergraph generation for multi-view semi-supervised classification.

Graph structure is widely used in the field of multi-view learning. Hypergraph which is a kind of ex...

Multi-Modality Sheep Face Recognition Based on Deep Learning.

To address the challenge of recognizing sheep faces of the same type, which exhibit significant simi...

Detecting arousals and sleep from respiratory inductance plethysmography.

PURPOSE: Accurately identifying sleep states (REM, NREM, and Wake) and brief awakenings (arousals) i...

Semi-supervised temporal attention network for lung 4D CT ventilation estimation.

Computed tomography (CT)-derived ventilation estimation, also known as CT ventilation imaging (CTVI)...

CLIC1 and IFITM2 expression in brain tissue correlates with cognitive impairment via immune dysregulation in sepsis and Alzheimer's disease.

BACKGROUND: Sepsis, a life-threatening condition driven by dysregulated host responses to infection,...

Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning.

Sepsis is a highly variable condition, and tracking leukocyte patterns may offer insights for tailor...

CHMMConvScaleNet: a hybrid convolutional neural network and continuous hidden Markov model with multi-scale features for sleep posture detection.

Sleep posture, a vital aspect of sleep wellness, has become a crucial focus in sleep medicine. Studi...

TCH: A novel multi-view dimensionality reduction method based on triple contrastive heads.

Multi-view dimensionality reduction (MvDR) is a potent approach for addressing the high-dimensional ...

A multi-domain constraint learning system inspired by adaptive cognitive graphs for emotion recognition.

Neuroscience shows that the brain stimulated by external information can induce functional responses...

Artificial intelligence-driven integration of multi-omics and radiomics: A new hope for precision cancer diagnosis and prognosis.

Despite advances in cancer diagnosis and treatment, the disease remains a major health challenge. In...

Integrative Multi-Omics Analysis Reveals Molecular Subtypes of Ovarian Cancer and Constructs Prognostic Models.

Ovarian cancer (OV) remains the most lethal gynecological malignancy. The aim of this study was to i...

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