Critical Care

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

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Subcategories: Sepsis
Showing 1-21 of 7,402 articles
Diabetic retinopathy classification using a multi-attention residual refinement architecture.

Diabetic Retinopathy (DR) is a complication caused by diabetes that can destroy the retina, leading ...

Mol-SGGI: an attention-guided comprehensive molecular multi-representation learning and adaptive fusion framework for molecular property prediction.

Molecular property prediction is pivotal for drug discovery, offering significant potential to accel...

Multimodal machine learning for risk-stratified bundled payments in spinal surgery.

Accurate prediction of financial metrics in spine surgery is crucial as healthcare transitions to va...

Learning spatio-temporal context for basketball action pose estimation with a multi-stream network.

Accurate athlete pose estimation in basketball is crucial for game analysis, player training, and ta...

Synthesized myelin and iron stainings from 7T multi-contrast MRI via deep learning.

Iron and myelin are key biomarkers for studying neurodegenerative and demyelinating brain diseases. ...

How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a Behavioural Artificial Intelligence Technology (BAIT) approach.

OBJECTIVES: To identify relevant objective variables for retrospective identification of 'suspected ...

Human respiratory simulation based on 3D modelling - a review.

Accurate simulation of respiratory dynamics is essential for advancing the diagnosis and treatment o...

Multi-fidelity graph neural networks for predicting toluene/water partition coefficients.

Accurate prediction of toluene/water partition coefficients of neutral species is crucial in drug di...

ADAM-DETR: an intelligent rice disease detection method based on adaptive multi-scale feature fusion.

Rice diseases pose a severe threat to global food security, while traditional detection methods suff...

3D IntelliGenes: AI/ML application using multi-omics data for biomarker discovery and disease prediction with multi-dimensional visualization.

BACKGROUND: The cutting-edge artificial intelligence (AI) and machine learning (ML) techniques have ...

Deep learning approach for automated hMPV classification.

Human metapneumovirus (hMPV) is a significant cause of respiratory illness, particularly in children...

Artificial intelligence-driven decision support for patients with acute respiratory failure: a scoping review.

BACKGROUND: Artificial intelligence (AI) has emerged as a promising tool for decision support in man...

Land use classification using multi-year Sentinel-2 images with deep learning ensemble network.

Accurate land use classification is essential for urban planning, environmental monitoring, and agri...

Real-time prediction of intensive care unit patient acuity and therapy requirements using state-space modelling.

Intensive care unit (ICU) patients often experience rapid changes in clinical status, requiring time...

Enhancing B-mode-based breast cancer diagnosis via cross-attention fusion of H-scan and Nakagami imaging with multi-CAM-QUS-driven XAI.

OBJECTIVE: B-mode ultrasound is widely employed for breast lesion diagnosis due to its affordability...

Multi-scale Autoencoder Suppression Strategy for Hyperspectral Image Anomaly Detection.

Autoencoders (AEs) have received extensive attention in hyperspectral anomaly detection (HAD) due to...

ICU-EEG Pattern Detection by a Convolutional Neural Network.

OBJECTIVE: Patients in the intensive care unit (ICU) often require continuous EEG (cEEG) monitoring ...

Lightweight grape leaf disease recognition method based on transformer framework.

Grape disease image recognition is an important part of agricultural disease detection. Accurately i...

Multi-module UNet++ for colon cancer histopathological image segmentation.

In the pathological diagnosis of colorectal cancer, the precise segmentation of glandular and cellul...

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